Current Issue

  • Survey PaperFebruary 1, 2024

    Similar but Different: A Survey of Ground Segmentation and Traversability Estimation for Terrestrial Robots

    Hyungtae Lim, Minho Oh, Seungjae Lee, Seunguk Ahn, and Hyun Myung*

    International Journal of Control, Automation, and Systems 2024; 22(2): 347-359

    https://doi.org/10.1007/s12555-023-0826-4

    Abstract

    Abstract : With the increasing demand for mobile robots and autonomous vehicles, several approaches for long-term robot navigation have been proposed. Among these techniques, ground segmentation and traversability estimation play important roles in perception and path planning, respectively. Even though these two techniques appear similar, their objectives are different. Ground segmentation divides data into ground and non-ground elements; thus, it is used
    as a preprocessing stage to extract objects of interest by rejecting ground points. In contrast, traversability estimation identifies and comprehends areas in which robots can move safely. Nevertheless, some researchers use these terms
    without clear distinction, leading to misunderstanding the two concepts. Therefore, in this study, we survey related literature and clearly distinguish ground and traversable regions considering four aspects: a) maneuverability of robot
    platforms, b) position of a robot in the surroundings, c) subset relation of negative obstacles, and d) subset relation of deformable objects.

  • Regular PapersFebruary 1, 2024

    Mathematical Modeling and Analysis of a Piston Air Compressor of a Railway Vehicle for Abnormal Data Generation

    Myeong-Joon Kim, Hyun-Jik Cho, and Chul-Goo Kang*

    International Journal of Control, Automation, and Systems 2024; 22(2): 360-372

    https://doi.org/10.1007/s12555-023-0080-9

    Abstract

    Abstract : To effectively implement condition-based maintenance for the air compressor in a railway vehicle, a thorough understanding of its fault characteristics and the collection of abnormal data is crucial. However, obtaining sufficient abnormal data from actual railway vehicles is challenging due to the rarity of air compressor failures in commercial railway services. This paper presents a detailed mathematical model of a two-stage piston air compressor that takes into account heat transfer effects. The mathematical model and the fault characteristics of the air compressor are analyzed through MATLAB simulation studies. The accuracy of the proposed model and analysis is verified by comparing it to real pressure data collected from a commercial Seoul subway train. The paper also generates abnormal data through simulations for specific fault conditions, including discharge valve leakages, air cooler malfunctions and pressure switch malfunctions.

  • Regular PapersFebruary 1, 2024

    Analysis of Networked Control System With Integer-order and Fractional-order PID Controllers

    Vijay R. Dahake*, Mukesh D. Patil, and Vishwesh A. Vyawahare

    International Journal of Control, Automation, and Systems 2024; 22(2): 373-386

    https://doi.org/10.1007/s12555-023-0181-5

    Abstract

    Abstract : In distributed closed-loop control systems like wireless networked control systems (WNCS), handling sensor-to-controller delay, controller-to-actuator delay, packet dropouts at the controller, and packet dropouts at the actuator is challenging. Hence in the wireless environment, the superiority and flexibility of fractional-order PID controllers are investigated for integer order-integer order (IO-IO), fractional order-integer order (FO-IO), integer order-fractional order (IO-FO), and fractional order-fractional order (FO-FO) wireless networked control systems in this paper. The kernel and standalone approaches are used for wireless channels IEEE 802.11b (WLAN) and IEEE 802.15.4. It has been shown with extensive simulation studies that a fractional-order PID controller eliminates a large overshoot in output response compared to an integer-order PID controller in some systems. Further, it also considerably reduces rise time and settling time. Performances of FO-PID and IO-PID controllers are investigated under parametric uncertainty of integer and fractional-order plants. Also, the performances of FO-PID and IO-PID controllers are investigated in the presence of external disturbance at the input of integer and fractional-order plants.

  • Regular PapersFebruary 1, 2024

    Optimal Regulation Performance of MIMO Networked Time-delay Systems With Limited Bandwidth and Interference Signals

    Qianhao Li, Qingsheng Yang, Xisheng Zhan*, and Jie Wu

    International Journal of Control, Automation, and Systems 2024; 22(2): 387-395

    https://doi.org/10.1007/s12555-022-0537-2

    Abstract

    Abstract : In this paper, we investigate the optimal regulation performance of networked time delay systems with limited bandwidth and interference signals. Communication networks are primarily influenced by parameters including bandwidth, packet dropouts, coding and decoding, interference signals, and channel noise. For a given system, non-minimum phase zeros, unstable poles, and time delay are considered. The corresponding regulation performance expressions are derived using coprime decomposition, spectral decomposition techniques, and norm correlation theory in the frequency domain. Results indicate that regulation performance is dependent on the location and direction of non-minimum phase zeros and unstable poles of a given system, as well as the internal time delay of the controlled plant. In addition, network communication parameters such as bandwidth, channel noise, packet dropouts, and external interference signals influence the performance of the regulation. Finally, simulation examples are provided to demonstrate the theory’s validity.

  • Regular PapersFebruary 1, 2024

    Recursive Quantization-based Event Triggered Observer for Networked Systems Under Network Congestion and Packet Loss

    Biao Xiang, Xia Liu*, and Yong Chen

    International Journal of Control, Automation, and Systems 2024; 22(2): 396-405

    https://doi.org/10.1007/s12555-022-0669-4

    Abstract

    Abstract : Focusing on the network congestion and packet loss in the networked systems, a recursive quantizationbased event triggered observer (RQETO) is proposed in this paper. The RQETO is composed of the local observer and the remote observer. The local observer reduces the amount of transmitted measured output by incorporating the event triggered strategy with the improved quantization mechanism. The improved quantization mechanism is based on the recursive algorithm, which can constrain the quantization error within the maximum allowable quantization error. The remote observer compensates the impact of packet loss by Bernoulli distribution model and hold-input strategy after receiving the data transmitted by the local observer. Through the local observer and the remote observer, network congestion is adequately alleviated, and the impact of packet loss is compensated while obtaining the accurate state estimation. The stability of the RQETO is proved by Lyapunov method, and the effectiveness of the RQETO is demonstrated on brushless direct current motor and Net-Con PC104 experimental platform.

  • Regular PapersFebruary 1, 2024

    Dynamic Event-triggered Fuzzy Filtering for Semi-linear Parabolic PDE Systems: A Reduced-order Approach

    Zhen Zhang, Xiaona Song*, and Xiangliang Sun

    International Journal of Control, Automation, and Systems 2024; 22(2): 406-418

    https://doi.org/10.1007/s12555-021-1015-y

    Abstract

    Abstract : This paper investigates dynamic event-triggered fuzzy reduced-order filtering for a class of nonlinear semi-linear parabolic partial differential equation (PDE) systems. First, the considered systems are reconstructed by a Takagi-Sugeno (T-S) fuzzy model based on the sector nonlinearity approach. Furthermore, a dynamic eventtriggered mechanism is developed to improve network resource utilization. Based on the non-parallel distribution compensation principle, several theorems that guarantee the augmented system’s asymptotic stability with L2-L∞ performance are provided. Finally, two examples are introduced to illustrate the effectiveness of the proposed method.

  • Regular PapersFebruary 1, 2024

    Double-step Acceleration Input Shaping Anti-sway Control Based on Phase Plane Trajectory Planning

    Wenbo Huang, Wangqiang Niu*, Hongfen Bai, and Wei Gu

    International Journal of Control, Automation, and Systems 2024; 22(2): 419-429

    https://doi.org/10.1007/s12555-021-1112-y

    Abstract

    Abstract : In order to improve transport efficiency and enhance the safety of the crane system, it is required that the trolley can reach the desired position fast enough, while the load swing needs to be within the bounded limits. To achieve these goals, a novel double-step acceleration strategy with equal acceleration amplitude and acceleration time, and unequal acceleration amplitude and acceleration time is proposed for input shaping anti-sway control based on phase plane trajectory planning. Specifically, the desired double-step acceleration signal is designed using an input shaper, and then the phase plane trajectory of the load swing angle is planned using the phase plane method. The geometric constraints of the phase plane trajectory and the physical constraints of the crane allow the amplitude and switching time of the double-step acceleration to be solved. The final simulation results show that the proposed control method achieves an effective anti-sway effect on the container crane.

  • Regular PapersFebruary 1, 2024

    H_/H∞ Filtering Fault Detection for Asynchronous Switched Discrete-time Linear Systems With Mode-dependent Average Dwell Time

    Xian-Zhi Hao and Jin-Jie Huang*

    International Journal of Control, Automation, and Systems 2024; 22(2): 430-445

    https://doi.org/10.1007/s12555-022-0343-x

    Abstract

    Abstract : The filtering fault detection problem for asynchronous switched discrete-time linear systems with modedependent average dwell time (MDADT) is investigated in this paper. A series of mode-dependent fault detection filters are designed with respect to each subsystem and are equipped with the switched system to obtain an augmented switched system. For the fact that the switching of the filter lags behind that of the subsystem frequently in actual situations, the resulting augmented switched system is consequently converted into an asynchronous augmented switched system. To guarantee the globally uniformly exponentially stability (GUES) and the H_/H∞ performance of the asynchronousfiltering fault detection system, multiple Lyapunov functional and MDADT techniques are then used. The starting instants set of the subsystem is proposed to make it more convenient to apply the MDADT technique. The sufficient conditions for the existence of the designed filter and stability of asynchronous augmented switched systems are given in terms of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed methodology is demonstrated by two examples.

  • Regular PapersFebruary 1, 2024

    A Novel Stochastic Model Predictive Control Considering Predictable Disturbance With Application to Personalized Adaptive Cruise Control

    Xuqiang Qiao, Ling Zheng, Yinong Li*, Ziwei Zhang, Jie Zeng, and Hao Zheng

    International Journal of Control, Automation, and Systems 2024; 22(2): 446-459

    https://doi.org/10.1007/s12555-022-0389-9

    Abstract

    Abstract : A novel stochastic model predictive control (SMPC) scheme is proposed for automotive scenes based on high-performance and practical motion state prediction method. The significant properties of the proposed scheme are that: 1) it can accurately predict disturbances within the prediction horizon, and 2) the prediction results can be considered into the optimizing process to obtain a more efficient and accurate controller. As a result, the proposed adaptive cruise control (ACC) system can ensure driving safety and improve tracking accuracy and comfort performance while satisfying different driving styles. In detail, a large amount of naturalistic driving data is collected based on a real vehicle test platform at first. Then an adaptive optimization Gaussian process regression (AOGPR) is developed and trained with real measurements to predict the motion states of the preceding vehicle. The prediction module is embedded in SMPC to bind the collision conditions, tighten the states and finally construct a novel controller, i.e., AOGPR-SMPC controller. A bidirectional LSTM (BiLSTM) network is trained and tested for online recognizing driving styles to satisfy personalized car-following needs. The simulation and field tests verify and evaluate the proposed controller. The results demonstrate that the ACC system could realize personalized carfollowing according to the driver’s driving style, and the proposed controller can obtain better tracking accuracy and comfort performance compared with the GPR-SMPC controller and MPC controller.

  • Regular PapersFebruary 1, 2024

    Abstract

    Abstract : In a high-speed operation, the iron loss of motor cannot be neglected since it may not be small enough. The existence of iron loss will lead to unknown nonlinearities and model uncertainties. Additionally, the existence of output delay in the system will bring speed fluctuation, which may degrade the control efficiency and even cause system instability. Hence, with the aid of continuous form characteristic model, this article provides the adaptive controller to address the control problem for high-speed permanent magnet synchronous motor (HSPMSM) system subject to time delay and plant uncertainties, simultaneously. Specifically, by employing characteristic model is more conducive to the design of controller, that is, the characteristic model only includes the input and output of the system, and the current is not required for parameter estimation. In addition, the proposed controller can deal with time delay, parametric uncertainties and uncertain nonlinearities at the same time. Furthermore, the numerical simulation results demonstrate the effectiveness and robustness of the proposed control strategy.

  • Regular PapersFebruary 1, 2024

    Finite-time Issue of Discrete-time Linear Switched Systems With Partial Finite-time Unstable Modes Based on an Inverse Weighted Switching Scheme

    Yunpeng Zhan, Ruihua Wang*, and Shumin Fei

    International Journal of Control, Automation, and Systems 2024; 22(2): 475-488

    https://doi.org/10.1007/s12555-022-0498-5

    Abstract

    Abstract : The work proposes a multiple convex Lyapunov function and an inverse weighted switching scheme to investigate the finite-time stability and finite-time boundedness for a class of discrete-time switched linear systems with partial finite-time unstable modes. A multiple convex Lyapunov function is put forth by constructing a convex combination of positive definite matrices, which can relax the restricted conditions of the Lyapunov function and make it carry more decision variables than traditional Lyapunov function methods. Besides, the inverse weighted switching scheme is devised by summing the reciprocal of each dwell time with weighting coefficients, by which tighter dwell time bounds are ensured. On the basis of the new Lyapunov function and switching scheme, the finitetime control for a class of switched linear systems with partial finite-time unstable modes is addressed. Different from other researches that require all subsystems to be controllable, we only require the existence of one controllable subsystem. In the end, two numerical examples and a tunnel diode circuit example are provided to verify the effectiveness of the developed results.

  • Regular PapersFebruary 1, 2024

    Adaptive Second-order Sliding Mode Control of Electrical Throttles Based on Online Zero-crossing Checking

    Yun Long, Yan-Min Wang, Chong Yao*, En-Zhe Song, and Quan Dong

    International Journal of Control, Automation, and Systems 2024; 22(2): 489-502

    https://doi.org/10.1007/s12555-021-0876-4

    Abstract

    Abstract : In this paper, an adaptive second-order sliding mode control approach is proposed for the performance improvement of electronic throttles (ET). Based on the traditional twisting approach, a novel adaptation mechanism based on the online zero-crossing checking is contained in the modified approach to make the control magnitude of the controller at the minimum admissible level. The idea behind it is to calculate the number of zero-crossings of the sliding surface in real time. The guaranteed stability condition and convergence region of the system are also deduced. In order to further prove its high adaptation capability, the commonly used adaptation mechanism called the Lyapunov-based type is also introduced for comparative study. Simulations and experiments validate the proposed approach with the advantages of chattering elimination, high speed and accuracy in the control of ET systems.

  • Regular PapersFebruary 1, 2024

    Robust Tracking Control for Permanent Magnet Linear Synchronous Motors With Unknown Uncertainties via Sliding Mode Approach

    Dongxue Fu, Ximei Zhao*, and Jianguo Zhu

    International Journal of Control, Automation, and Systems 2024; 22(2): 503-516

    https://doi.org/10.1007/s12555-022-0438-4

    Abstract

    Abstract : This paper proposes a novel robust super-twisting nonsingular fast terminal sliding mode control method for high precision position tracking of permanent magnet linear synchronous motor (PMLSM). Based on the position tracking error of PMLSM, a nonsingular fast terminal sliding mode variable is constructed to avoid the singularity and achieve the convergence of the position error in a finite time. To improve the convergence speed of the super-twisting algorithm and solve the gain overestimation problem of the existing algorithm, a dual-layer nested adaptive adjustment law based on the super-twisting scheme is proposed, which does not need the information of the unknown uncertainties. While ensuring that the conditions of the existence of the sliding mode hold, the control gain is made as small as possible to obtain a continuous switching control law to suppress the effect of the chattering phenomenon. The Lyapunov stability proves the robustness and convergence of the system. Experimental results confirm the effectiveness and feasibility of the designed position tracking control scheme.

  • Regular PapersFebruary 1, 2024

    Barrier Lyapunov Functions-based Output Feedback Control for a Class of Nonlinear Cascade Systems With Time-varying Output Constraints

    Jing Yang, Jie Zhang, Zhongcai Zhang, and Yuqiang Wu*

    International Journal of Control, Automation, and Systems 2024; 22(2): 517-526

    https://doi.org/10.1007/s12555-022-0955-1

    Abstract

    Abstract : In this study, a class of nonlinear systems with integral input to state stability (iISS) inverse dynamics and unknown control direction are examined for the issue of time-varying asymmetric output constraints of adaptive output feedback controller. To deal with unmeasured state variables and unknown directions, the state observer is constructed using a Rickati matrix differential equation with time variation. A backstepping-based method is recommended for establishing the dynamic output feedback control law. By ensuring boundedness for the timedependent barrier Lyapunov function (BLF) in the closed loop, we may not only maintain the boundedness and stability of other signals, but also avoid breaking the time-varying asymmetric constraint of the output. Finally, simulation analyses are used to confirm the scheme’s efficacy.

  • Regular PapersFebruary 1, 2024

    General Stabilization for Stochastic System With Input Delay and Multiplicative Noise: Continuous-time Case

    Cheng Tan*, Jianying Di, Zhengqiang Zhang, and Wing Shing Wong

    International Journal of Control, Automation, and Systems 2024; 22(2): 527-536

    https://doi.org/10.1007/s12555-022-1184-3

    Abstract

    Abstract : This paper investigates the general stabilization issues for continuous-time stochastic dynamics whose input delay and multiplicative noise in control variable exist simultaneously. On the one hand, we present a set of necessary and sufficient conditions for stabilizing the considered stochastic dynamics in mean-square sense. Different from many previous works, one significant innovation is that our control policy is designed as the feedback of an extended state that contains the current available state and some past control information. On the other hand, another important innovation is that we for the first time generalize the notions of critical stabilization and essential destabilization to stochastic time-delay model in terms of spectral analysis technique, while the related necessary and sufficient stabilization conditions are derived respectively.

  • Regular PapersFebruary 1, 2024

    Co-design of Anti-windup Compensator and a Novel Saturation-based Dynamic Event-triggered Mechanism for Asymmetric Saturated System

    Hongchao Li*, Huimin Deng, Mengfan Li*, and Nan Zhang

    International Journal of Control, Automation, and Systems 2024; 22(2): 537-547

    https://doi.org/10.1007/s12555-022-0504-y

    Abstract

    Abstract : This paper addresses the co-design of anti-windup compensator and a novel saturation-based dynamic event-triggered condition for asymmetric saturated system. Asymmetric saturation frequently appears in practical systems, which may seriously degrade the system performance. For the systems with undetectable state, dynamic output feedback controller is employed in this paper. A saturation-based dynamic event-triggered mechanism related to the upper and lower bounds of asymmetric saturation is proposed in this paper, which has better performance in reducing the event-triggered number than static event-triggered condition. In addition, the minimum triggering time interval is calculated to avoid Zeno behavior. An optimization problem is formulated to maximize estimated stable region for the closed-loop system. Finally, the proposed results are illustrated by a numerical example.

  • Regular PapersFebruary 1, 2024

    Parameter Estimation Method for Generalized Time-varying Systems With Colored Noise Based on the Hierarchical Principle

    Shutong Li, Yan Ji*, and Anning Jiang

    International Journal of Control, Automation, and Systems 2024; 22(2): 548-559

    https://doi.org/10.1007/s12555-022-0867-0

    Abstract

    Abstract : For generalized time-varying systems with colored noise, the difficulty of identification lies in timevarying parameters and colored noise. The recursive estimation problem of a controlled autoregressive generalized time-varying system with autoregressive moving average noise is studied. By means of the hierarchical principle, the identification model is decomposed into two subsystems with fewer variables and different characteristics, which simplifies the original model and processes the colored noise based on the idea of the auxiliary model. Then a two-stage auxiliary model-based recursive least squares (TS-AM-RLS) algorithm is proposed, which realizes the parameter estimation of the subsystem based on the least squares method. In order to improve the identification accuracy and convergence speed, the scalar innovation is extended to the innovation vector, and a multi-innovation least squares algorithm is proposed by using the multi-innovation identification theory. A numerical experiment is given to illustrate the performances of the proposed algorithms.

  • Regular PapersFebruary 1, 2024

    Abstract

    Abstract : In this paper, it is proved that an unstable highly nonlinear hybrid stochastic functional differential equation with infinite delay (HNHISFDE) can be stabilized by designing a controller that not only depends on discretetime state observations, but only produces different time lags in each observation. Firstly, common conditions are imposed on the original system to ensure the existence and uniqueness of the solution. Secondly, the design method of delay feedback control is presented to stabilize a class of HNHISFDEs. Notably, new assumptions based on Lyapunov functional and M-matrix methods are provided to construct the controller step by step. Then, the sufficient criteria of H∞ stabilization, asymptotic stabilization and exponential stabilization are established by applying the Lyapunov stability theory. Finally, the effectiveness of the theoretical results is illustrated by a numerical example.

  • Regular PapersFebruary 1, 2024

    Abstract

    Abstract : In this paper, we analyze robust stability of differential dynamical system with deviating argument in derivative part. By using inequality technique and stochastic analysis idea, we obtain the upper bounds of the interval length of deviating argument and the noise intensity, respectively. First, it is proved theoretically that for a given exponentially stable differential dynamical system (DDS), if the interval length of deviating argument is lower than the upper bound, DDS with deviating argument will still maintain exponentially stable. In addition, it is also proved that for a given exponentially stable DDS, if the interval length of deviating argument and noise intensity are lower than the upper bound, stochastic DDS (SDDS) with deviating argument will remain exponentially stable. Finally, theoretical findings are supported by two examples.

  • Regular PapersFebruary 1, 2024

    Neuro-adaptive Event-triggered Optimal Control for Power Battery Systems With State Constraints

    Xiaoxuan Pei, Kewen Li, and Yongming Li*

    International Journal of Control, Automation, and Systems 2024; 22(2): 581-592

    https://doi.org/10.1007/s12555-022-1127-z

    Abstract

    Abstract : This paper investigates an adaptive neural networks (NNs) event-triggered optimal control method for the second-order resistance capacitance (RC) equivalent circuit system with state constraints. The NNs are used to estimate the unknown nonlinear functions. In order to constrain the states within the designed boundary in optimal control strategy, the barrier Lyapunov function (BLF) method is taken into account. Furthermore, to economic the transmission resources, the adaptive NNs event-triggered optimizing control strategy is developed by employing the relative threshold strategy. The proposed optimal control strategy is not only able to satisfy the stability of closedloop system, but also can guarantee the performance index functions minimized when all states remain within the given boundaries. Finally, the effectiveness of the suggested control method is demonstrated by simulation.

  • Regular PapersFebruary 1, 2024

    Input-to-state Practical Stability of Event-triggered Estimators for Discrete-time Recurrent Neural Networks With Unknown Time-delay

    Yougang Wang, Yashuan Liu, and Sanbo Ding*

    International Journal of Control, Automation, and Systems 2024; 22(2): 593-602

    https://doi.org/10.1007/s12555-022-0598-2

    Abstract

    Abstract : In this paper, event-triggered estimators are designed for discrete-time recurrent neural networks (RNNs) with unknown time-delay. Owing to the diversity and complexity of time-delays, it is difficult to accurately predict their information. Under the boundedness of activation functions, the delay-depend term is regarded as a bounded nonlinear disturbance. Two event-triggered estimators are designed to estimate the neuron states. The first one considers the case that the system states are subject to unknown time-delay, and the second one deals with the case that both the system states and measurement outputs are subject to unknown time-delay. The sufficient conditions are developed to guarantee the input-to-state practical stability of estimation error systems. Finally, the dynamic event-triggered strategy is introduced to further reduce the events. Two numerical examples are given to show the validity of the developed scheme.

  • Regular PapersFebruary 1, 2024

    PCA Fault Isolation Using Interval Reconstruction

    Raoudha Bel Hadj Ali*, Anissa Ben Aicha, Kamel Belkhiria, and Gilles Mourot

    International Journal of Control, Automation, and Systems 2024; 22(2): 603-614

    https://doi.org/10.1007/s12555-023-0170-8

    Abstract

    Abstract : Fault detection and isolation (FDI) based on principal component analysis (PCA) has been widely developed. However, PCA is used for FDI without regard to model uncertainties. In this paper, the model uncertainties being represented as interval, we propose to perform multiple fault isolation by extending the reconstruction principle to interval PCA model. Variable reconstructions can be expressed as a problem of solving a system of interval linear equations. From these reconstructions, interval structured residuals are designed in order to identify the set of faulty variables. However, the number and directions of faults being a priori unknown, a multiple fault isolation strategy is proposed in order to alleviate analyzing all combinations related to simultaneous variable reconstructions. Our innovative method is illustrated on a simulation example. The interest of taking into consideration the model uncertainties on FDI will be illustrated.

  • Regular PapersFebruary 1, 2024

    A Spraying Path Planning Algorithm Based on Point Cloud Segmentation and Trajectory Sequence Optimization

    Ru-Xiang Hua*, Hong-Xuan Ma, Wei Zou, Wei Zhang, and Zhuo Wang

    International Journal of Control, Automation, and Systems 2024; 22(2): 615-630

    https://doi.org/10.1007/s12555-022-0203-8

    Abstract

    Abstract : Spraying trajectory planning is a key and challenging work for intelligent spraying robot. In order to effectively fulfill spraying on complex surfaces without CAD model, a novel spraying trajectory planning method based on segmentation and trajectory sequence optimization is proposed in this paper, which is mainly composed by three steps: surface segmentation, trajectories generation and trajectories connection. In surface segmentation, a method named regional growth with minimum curvature point (RGMCP) is proposed to segment a 3D entity into different subsurfaces by taking normals and curvatures into consideration simultaneously. In trajectories generation step, an intersection of plane and point cloud (IPPC) algorithm is used to generate the optimal spraying trajectory for each segmented subsurface. Finally, for trajectories connection, a sequence optimization algorithm based on swap-evolution particles (SOSP) is proposed to connect all the subsurface trajectories as a complete spraying one in an optimum manner by regarding it as a sequence optimization problem. The effectiveness of the proposed method is validated by simulation and practical experiment simultaneously. Comparatively, our method can improve the efficiency of a spray task with 367 trajectories and 627 s time-consuming to 215 trajectories and 413 s, while the coating thickness variances are lowered from 51.9 µm2 and 30.4 µm2 to 3.64 µm2 and 7.89 µm2 respectively, which shows that the proposed method is more effective and can keep better coating thickness uniformity.

  • Regular PapersFebruary 1, 2024

    Search-based Path Planning and Receding Horizon Based Trajectory Generation for Quadrotor Motion Planning

    Bo Zhang, Pudong Liu, Wanxin Liu, Xiaoshan Bai*, Awais Khan, and Jianping Yuan

    International Journal of Control, Automation, and Systems 2024; 22(2): 631-647

    https://doi.org/10.1007/s12555-022-0742-z

    Abstract

    Abstract : This paper proposes a receding horizon based motion planning method, which allows a sensoryconstrained quadrotor to dynamically plan obstacle-avoiding trajectories in unknown complex environments. First, a two-process search method is proposed to generate an initial feasible path satisfying the dynamics of the quadrotor. Second, the path smoothness is improved by solving a nonlinear optimization problem considering path safety and smoothness. Then, a uniform B-spline is used to interpolate the path with a receding horizon to achieve a safe and dynamically feasible trajectory with minimum trajectory time by solving an optimization problem. Finally, a time adjustment method is proposed based on the relationship between the distance of the B-spline trajectory and the obstacles. Extensive simulation results illustrate that the designed method doubles the safety range, defined as the minimum distance between the quadrotor and the obstacles, and consumes less than 70% of computational running time compared with the state-of-the-art. Outdoor flight experiments performed with a vision-based quadrotor show the satisfying performance of the motion planning approach.

  • Regular PapersFebruary 1, 2024

    Backstepping Based Trajectory Tracking Control of a TBM Steel Arch Splicing Manipulator

    Yuxi Chen, Guofang Gong*, Xinghai Zhou, Yakun Zhang, and Weiqiang Wu

    International Journal of Control, Automation, and Systems 2024; 22(2): 648-660

    https://doi.org/10.1007/s12555-021-0965-4

    Abstract

    Abstract : At present, the splicing of steel arches for open-type TBM suffers from the problems of labor-intensive, time-consuming, low efficiency and greater potencial risk to workers. Rock-fall and collapse caused by untimely support is still one of the main construction accidents. In this paper, a novel steel arch splicing manipulator is developed for unmanned and automated steel arch splicing, and a backstepping method based cascade control strategy is proposed to improve the trajectory tracking control performance. Firstly, the inner-loop controller is designed to compensate the flow coupling between each joint-driven hydraulic cylinder based on dynamic analysis and feedback linearization. Secondly, the adaptive robust controller is adopted for outer-loop controller design to deal with parametric uncertainties and external disturbances. Finally, the system stability is proved by Lyapunov function, then comparative experiments are conducted to verify the effectiveness and superiority of the proposed control scheme. It can be concluded that the proposed controller has a better trajectory tracking control performance, while the control input is much smoother than that of traditional PID controller.

  • Regular PapersFebruary 1, 2024

    Research on Human-robot Shared Control of Throat Swab Sampling Robot Based on Intention Estimation

    Ying-Long Chen*, Fu-Jun Song, Heng-Fei Yan, Peng-Yu Zhao, and Yong-Jun Gong

    International Journal of Control, Automation, and Systems 2024; 22(2): 661-675

    https://doi.org/10.1007/s12555-022-0728-x

    Abstract

    Abstract : With the spread and persistence of COVID-19, pharyngeal swab sampling, is an important link in nucleic acid testing, which is characterized by a high workload and susceptibility to infection. Therefore, it is necessary for medical workers to use medical robots instead of manual site sampling for collaborative sampling. However, the traditional teleoperation has difficulty ensuring the closed-loop performance due to the delay of the actual process, along with the weak control performance; Moreover, a robot cannot accurately plan and track sampling paths due to sensor accuracy and the changes in patient pharyngeal posture. The paper proposes a human-robot shared control strategy based on intention estimation, introducing the human intention as a reference, and the operator and robot work together to solve various significant problems during sampling. The human-robot negotiation based on the method includes the human judgement and perception and the robot into the invasion task. Through, the shared control based on the operator intention estimation, the robot can operate the obstacle avoidance and approach the target contact point remotely. Finally, two kinds of experiments of invasion process of throat swab sampling are implemented: a static target invasive experiment and a dynamic target invasive experiment, aiming at two different sampling conditions. Compared with the robotic independent control sampling, the time consumption in the two experiments is reduced by 34.8% and 41.6%, respectively, and the ultimate target position is basically within the scope of sampling field (where the range of the posterior pharynx wall < 20 mm). Thus, the sampling rate can reach 100%. Compared with independent control sampling by humans, the time consumption of the two experiments is respectively reduced by 15.9% and 42.3% on average, and the target position accuracy and sampling rate are quite close. Experimental results show that the control strategy improves the speed, flexibility, and intelligence of task execution compared to common sampling methods, laying the foundation for low-cost human-robot collaborative sampling.

  • Regular PapersFebruary 1, 2024

    Auditory Feature Driven Model Predictive Control for Sound Source Approaching

    Zhiqing Wang, Wei Zou*, Wei Zhang, Hongxuan Ma, Chi Zhang, and Yuxin Guo

    International Journal of Control, Automation, and Systems 2024; 22(2): 676-689

    https://doi.org/10.1007/s12555-022-0616-4

    Abstract

    Abstract : Sound source approaching is a typical task for the robot with auditory sensing. Many existing methods are based on sound source localization (SSL), and utilize the explicit location as the control input. To reduce the localization computation cost and improve the robustness against noise and reverberation, we propose a novel auditory feature driven model predictive control (AFD-MPC) method, which directly uses the auditory feature as the control input. First, a new convolution-ternarization based interaural time difference (CT-ITD) estimation method is proposed, which is more robust to noise and reverberation by eliminating signal spikes and irrelevant components. Second, a new system model is derived and established, which directly links the robot motions and the interaural time difference (ITD) feature. Third, AFD-MPC is realized based on the proposed CT-ITD feature estimation and system model. The states at multiple future time steps are predicted based on the system model, and a control objective function considering both target approaching and motion smoothness is designed. By involving the multi-step future states in the control objective function, the control outcome is more smooth on motion trajectory and more robust to instantaneous interferences. A series of experiments such as static and dynamic sound source approaching are conducted on a mobile robot equipped with a small-sized 6-microphone array to validate the effectiveness of our methods.

  • Regular PapersFebruary 1, 2024

    A Comparative Field Study of Global Pose Estimation Algorithms in Subterranean Environments

    Nikolaos Stathoulopoulos*, Anton Koval, and George Nikolakopoulos

    International Journal of Control, Automation, and Systems 2024; 22(2): 690-704

    https://doi.org/10.1007/s12555-023-0026-2

    Abstract

    Abstract : In this article, we perform a novel and extended field evaluation of the state-of-the-art algorithmic frameworks’ performance on global pose estimation. More specifically, we focus on relocalizing a mobile robot in a pre-built 3D point cloud map of a large subterranean environment. The evaluation is divided into two parts. The first part consists of multiple simulations performed in two different Gazebo SubT worlds, where one is flat with various types of features, while another has uneven structure and is more textured. The second part is an experimental evaluation and takes place in a real-world underground tunnel. In all evaluation tests, the robot’s pose is selected in such a way that we can test the robustness, as well as the feature extraction capability, of each algorithm. The evaluation is carried out using three ROS packages: a) hdl_global_localization using both BBS and FPFH+RANSAC, b) LIO-SAM_based_relocalization, and c) Fast-LIO-Localization. Our goal is to have a clear view of each algorithm’s efficiency in terms of CPU load, memory allocation and time to relocalize, while we increase the size of the map and transverse the robot in different parts of the map.

  • Regular PapersFebruary 1, 2024

    RCLSTMNet: A Residual-convolutional-LSTM Neural Network for Forecasting Cutterhead Torque in Shield Machine

    Chengjin Qin*, Gang Shi, Jianfeng Tao*, Honggan Yu, Yanrui Jin, Dengyu Xiao, and Chengliang Liu

    International Journal of Control, Automation, and Systems 2024; 22(2): 705-721

    https://doi.org/10.1007/s12555-022-0104-x

    Abstract

    Abstract : During tunneling process, it is of critical importance to dynamically adjust operation parameters of shield machine due to changes of geological conditions. Cutterhead torque is one of the key load parameters, and its accurate prediction could adjust operational parameters including cutterhead rotational speed and tunneling speed in advance and avoid potential cutterhead jamming. Based on operation and state data collected by the monitoring system, we propose a residual-convolutional-LSTM neural network (RCLSTMNet) for forecasting cutter head torque in shield machine. On the basis of correlation analysis, parameters closely related to cutter head torque are selected as inputs by employing cosine similarity, which significantly reduces input dimension. Convolutional-LSTM neural network is fused and constructed for extracting deep useful features, while residual network module is utilized to avoid gradient disappearing and improve regression performance. Comparisons with recent data-driven cutterhead torque prediction methods are made on the actual engineering datasets, which demonstrate the presented RCLSTMNet outperforms the other data driven models in most cases. Moreover, the predicted curves of cutterhead torque using the proposed RCLSTMNet coincide with the actual curves much better than predicted curves using the other models. Meanwhile, the highest and average accuracy of RCLSTMNnet reach 98.1% and 95.6%, respectively.

  • Regular PapersFebruary 1, 2024

    Leader-following Non-fragile Consensus Control of Fuzzy Multi-agent Fractional Order Interval Systems

    Zhe Wang, Xuefeng Zhang*, Qing-Guo Wang, and Dingyu Xue

    International Journal of Control, Automation, and Systems 2024; 22(2): 722-729

    https://doi.org/10.1007/s12555-022-1009-4

    Abstract

    Abstract : The consensus control of fuzzy multi-agent fractional order interval systems (MA-FOISs) is proposed in this brief. Firstly, a new model of fuzzy MA-FOISs based on the non-fragile observer is presented. Then, by using the technologies of generalised matrix singular value decomposition (SVD) and linear matrix inequalities (LMIs), the sufficient conditions for determining the consensus of fuzzy MA-FOISs are given through the equivalence of the stability and the consensus of multi-agent systems (MASs). Moreover, when the actual system does not need to be described by the fuzzy set, the consensus conditions for the MA-FOISs are given. Finally, the validity of the results given are illustrated by the numerical example.

IJCAS
February 2024

Vol. 22, No. 2, pp. 347~729

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