Current Issue

  • Regular PapersJuly 1, 2024

    Convergence of a Democratic System Controlled by Dynamic Social Networks

    Seong-Jin Park

    International Journal of Control, Automation, and Systems 2024; 22(7): 2055-2063

    https://doi.org/10.1007/s12555-023-0515-3

    Abstract

    Abstract : This paper presents some graph-theoretic conditions for a democratic system controlled by a social network to converge to a regressive or progressive system over time. The democratic system is modeled as a finite state automaton, and a social network of agents is modeled as a directed graph. Agents are controllers making decisions to enable or disable events such that their objectives are to be met. Based on the individual decisions of agents, the final decision is made by the majority rule. Specifically, the conditions obtained imply two strategies for the groups of regressive or progressive agents to achieve their objectives: one is to prevent informed agents in other groups from influencing uninformed agents, and the other is to make at least one uninformed agent in every cycle follow the decisions of the group.

  • Regular PapersJuly 1, 2024

    Stable Degree Analysis for Profile of Networked Evolutionary Games With Disturbances

    Ziyun Wang, Shihua Fu, Jianjun Wang, Ling Yu, and Xiaoyu Zhao*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2064-2073

    https://doi.org/10.1007/s12555-023-0314-x

    Abstract

    Abstract : This paper studies the stable degree for profile of networked evolutionary games (NEGs) with disturbances by the semi-tensor product of matrices. Firstly, the algebraic formulation of an NEG with disturbances is established. Secondly, on the basis of algebraic formulation, some concepts about stable profile with disturbances are proposed, including strong k-degree stable and weak k-degree stable, and the corresponding criteria to detect the stable degree are presented. Thirdly, two algorithms for designing controls are given to make the stable profile achieves strong k-degree stable or weak k-degree stable. Finally, an example is given to illustrate the validity of the results.

  • Regular PapersJuly 1, 2024

    A Hybrid Systems Approach to Consensus of Nonlinear Multi-agent Systems With Self-triggered Output Feedback Control

    Wenliang Pei, Changchun Hua, Hailong Cui, and Guanglei Zhao*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2074-2084

    https://doi.org/10.1007/s12555-023-0409-4

    Abstract

    Abstract : This paper develops a hybrid systems approach to address the self-triggered leader-following consensus problem of nonlinear multi-agent systems. First, a distributed dynamic output feedback consensus control protocol is proposed, and a novel hybrid dynamic self-triggering mechanism (HDSTM), which can provide a pre-designable minimum triggering interval (MITI) for the adjacent events, is developed to reduce the usage of communication resources. Then, by means of internal variables, a hybrid model, including both flow and jump dynamics, is constructed to describe the closed-loop dynamics. Based on this hybrid model, Lyapunov-based consensus analysis and HDSTM design results are derived. Compared to the existing related works, the main superiority of the proposed approach is that the inter-event communication intervals can always be computed in advance and no less than the given MITI. Finally, a numerical example is provided to show the effectiveness.

  • Regular PapersJuly 1, 2024

    Fully-distributed Consensus Control of Multi-agent Systems Under Stochastic Hybrid Attacks on a Directed Graph

    Muhammad Mamoon*, Ghulam Mustafa, Naeem Iqbal, and Muhammad Rehan

    International Journal of Control, Automation, and Systems 2024; 22(7): 2085-2094

    https://doi.org/10.1007/s12555-023-0769-9

    Abstract

    Abstract : This study presents a consensus control method for generic linear multi-agent systems (MASs) subject to stochastic deception attacks on actuators and random denial of service (DoS) attacks over communication channels. In this case, the MASs are communicating over a compromised network where the attackers are performing random DoS attacks and injecting data into the control inputs. A fully-distributed robust-adaptive consensus protocol is designed for both types of stochastic cyber-attacks by taking into account the immediate partial information per node rather than global information and by accounting for the signals added by adversaries. To the best of the authors’ knowledge, a fully-distributed consensus control approach with adaptive gains (without requiring any global knowledge for the design) under hybrid cyber-attacks of stochastic nature over a directed graph has been addressed for the first time. Finally, simulation results are presented to further illustrate the theoretical results’ effectiveness.

  • Regular PapersJuly 1, 2024

    Observer-based Attitude Maneuver Control of Flexible Spacecraft: A Parametric Approach

    Liu Zhang, Quan-Zhi Liu, Guo-Wei Fan*, Xue-Ying Lv, Yu Gao, and Yang Xiao

    International Journal of Control, Automation, and Systems 2024; 22(7): 2095-2107

    https://doi.org/10.1007/s12555-022-0707-2

    Abstract

    Abstract : To address the problem of control performance degradation caused by flexible attachment vibrations and external disturbances during attitude maneuvering of flexible spacecraft, this paper proposes a parametric method for improving flexible spacecraft attitude maneuver control (AMC) based on a functional observer. The objective was to enhance the control accuracy and disturbance rejection. First, state expansion was carried out for flexible spacecraft systems affected by disturbances. A functional observer was designed for the system, and sufficient conditions for the existence of the observer were obtained. Furthermore, a controller was designed by using the state information of the observer, which included state feedback and feed-forward compensation. Based on the parametric solution of a class of generalized Sylvester equations (GSEs), the parametric expressions of the controller and observer were established. Finally, a numerical example of a flexible spacecraft proved the effectiveness of the design method. The method can effectively suppress flexible vibrations and external disturbances while also meeting the high-precision control requirements of the flexible spacecraft.

  • Regular PapersJuly 1, 2024

    Abstract

    Abstract : This paper investigates the adaptive finite-time tracking control problem for a class of constrained purefeedback systems with time-varying delays and unknown initial states. By designing a novel shifting function and using the state transformation, there is no need to know the initial value of states. Instead of employing barrier Lyapunov functions, the modified nonlinear state-dependent functions are constructed to solve the deferred state constraints, avoiding the feasibility conditions on virtual controllers. The effect of time-varying delays is eliminated by combining the radial basis function neural networks with a finite covering lemma, and the requirement that the derivative of time-varying delays should be less than one in Lyapunov-Krasovskii functional method is relaxed. The asymmetric saturation nonlinearity is solved by designing an auxiliary system. The system coordinate transformation is employed to solve the design difficulty brought by the nonaffine structure. Then, an adaptive finite-time tracking control scheme is developed based on the command filtered backstepping technique. The developed control scheme can not only make all states satisfy the asymmetric time-varying constraints after a predefined time, but also guarantee the finite-time tracking performance. Finally, simulation examples are given to demonstrate the effectiveness of the proposed scheme.

  • Regular PapersJuly 1, 2024

    Exponential Stability of Time-varying Switched Impulsive Nonlinear Systems Using Comparison Theorem

    Min Fan, Mengqian Liang, and Yazhou Tian*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2122-2129

    https://doi.org/10.1007/s12555-022-1205-2

    Abstract

    Abstract : This paper focuses on discussing the stability of time-varying switched impulsive nonlinear systems (TVSINSs). To conquer the difficulties induced by time-varying parameters, we firstly put forward comparison theorem associated with a method that doesn’t involve any Lyapunov function and is commonly utilized in positive systems to set up new stability criteria of TVSINSs under the average dwell time (ADT) switching. In comparison with recent results, the derived ones are not only in connection with state delay and impulse delay, but also possess less conservative conditions from the simulation analyses. In conclusion, the feasibility and superiority of the adopted approaches are testified by two appropriate examples.

  • Regular PapersJuly 1, 2024

    Sensorless Speed Tracking Control for Fault-tolerant Permanent Magnet Motor With Uncertainties in the Ship Shaftless Rim-driven Thruster System

    Hongfen Bai, Wenting Zhang, and Yiqun Xu*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2130-2141

    https://doi.org/10.1007/s12555-021-0420-6

    Abstract

    Abstract : The shaftless rim-driven thruster (RDT) has many attractive features and it would improve the faulttolerance of RDT to select the fault-tolerant permanent magnet motor (FTPMM) as the propulsion motor. The FTPMM works under severe marine environment and subjects to uncertainty and sensorless conditions. To overcome this problem, a sensorless speed tracking control is proposed for the FTPMM with general uncertainties, e.g., perturbing or time-varying parameters, unknown nonlinearities and bounded disturbances. Based on adaptive nonlinear damping, a robust adaptive observer is constructed to estimate the FTPMM speed. The proposed scheme ensures that all the dynamic signals of the closed system are bounded and it is not needed to estimate the uncertain parameters and disturbances of the system. Furthermore, the estimation errors and the tracking errors can converge to arbitrarily small values by adjusting design parameters. The effectiveness of the proposed scheme is verified by the simulation and experiment results. Furthermore, the stability of the control system and the robustness for the parameter uncertainty and load torque disturbance can be guaranteed.

  • Regular PapersJuly 1, 2024

    Polynomial Excitation Current Compensation Control for Dead Zone and Hysteresis of Three-way Proportional Pressure Reducing Valve

    Yan-He Song, Kai-Xian Ba*, Xin Chen, Yue-Yue Hao, Chao Ai, and Xiang-Dong Kong

    International Journal of Control, Automation, and Systems 2024; 22(7): 2142-2157

    https://doi.org/10.1007/s12555-022-0718-z

    Abstract

    Abstract : In this paper, aiming at the phenomenon that the dead zone and hysteresis of three-way proportional pressure reducing valve (TPPRV) will seriously affect the control accuracy of construction machinery, a polynomial excitation current compensation controller (PECC) is designed, which is novel and easy to realize in engineering. Firstly, the mathematical model of TPPRV is established, and the dead zone and hysteresis of TPPRV are quantitatively analyzed by using the performance test platform of proportional pressure reducing valve. Secondly, the design principle of PECC is expounded, and the controller model is deduced theoretically. The proposed PECC has two main advantages. One is that the method does not need to establish the nonlinear model of dead zone and hysteresis, and the other is that the method can compensate the dead zone and hysteresis simultaneously. Finally, the compensation control performance of PECC is verified by using the performance test platform of proportional pressure reducing valve. The experimental results show that PECC can greatly reduce the adverse effects of dead zone and hysteresis on TPPRV, and has great applicability under different working conditions. Relevant research results can significantly improve the proportional control accuracy of TPPRV, which has a certain engineering value.

  • Regular PapersJuly 1, 2024

    Adaptive Fault-tolerant Control of Platoons With Prescribed Tracking Performance

    Guanglei Zhao*, Gaoge Dai, Bingkang Peng, and Hailong Cui

    International Journal of Control, Automation, and Systems 2024; 22(7): 2158-2170

    https://doi.org/10.1007/s12555-023-0135-y

    Abstract

    Abstract : This article investigates a heterogeneous vehicular platoon control problem, in which prescribed tracking performance can be achieved, it is assumed that the vehicle subjects to asymmetric nonlinear actuator saturation, dead-zone nonlinearity and actuator faults. Based on improved exponential spacing policy, an adaptive fault-tolerant sliding-mode control scheme is proposed to guarantee individual vehicle stability, string stability and traffic flow stability. The hypothesis that the spacing errors at initial time are zero is removed by employing the novel exponential spacing policy. Furthermore, to attenuate the harmful effects of actuator faults, saturation and dead-zone nonlinearity, a compensation system based on radial basis neural network (RBFNN) is established. Finally, the effectiveness of the proposed control scheme is verified by simulation results.

  • Regular PapersJuly 1, 2024

    Prescribed Performance Control for the Lower Limb Exoskeleton With Time-varying State Constraints and Input Saturation

    Xianlei Zhang, Yan Zhang*, Qing Hu, Xuan Li, and Anjie Yang

    International Journal of Control, Automation, and Systems 2024; 22(7): 2171-2181

    https://doi.org/10.1007/s12555-023-0104-5

    Abstract

    Abstract : This paper studies the problem of prescribed performance tracking control for the lower limb exoskeleton under time-varying state constraints and input saturation. A prescribed performance control method is proposed to achieve the specified tracking accuracy within a preset time. Under the framework of system transformation, the control problem with specified performance and state constraints is transformed into the boundedness problem of auxiliary variables. Meanwhile, the hyperbolic tangent function is employed to deal with the input saturation. Through rigorous theoretical analysis, it can conclude that the tracking error converges to a prescribed region near the origin within a given time and all signals of the closed-loop system are bounded. The superiority of this control scheme is verified through a practical simulation example.

  • Regular PapersJuly 1, 2024

    Nonsingular Fixed-time Fault-tolerant Sliding Mode Control of Robot Manipulator With Disturbance Observer

    Xiaohan Fang*, Rong Cheng, Songsong Cheng, and Yuan Fan

    International Journal of Control, Automation, and Systems 2024; 22(7): 2182-2192

    https://doi.org/10.1007/s12555-022-0594-6

    Abstract

    Abstract : This paper presents a nonsingular sliding mode fault-tolerant control method with fixed-time convergence for a class of robot manipulators with uncertainties, external disturbances, and actuator failures. We estimate selffriction and external disturbances by designing a disturbance observer. Furthermore, based on the disturbance observer, we propose a sliding mode control method for the considered uncertain robot manipulator. Finally, the effectiveness of the proposed method is demonstrated by a numerical example.

  • Regular PapersJuly 1, 2024

    Event-triggered Hybrid Force Feedback Architecture With Tank-based Stabilization Method for Complicated Bilateral Teleoperation Tasks

    Zhitao Gao, Fangyu Peng, Chen Chen, Yukui Zhang, Yu Wang, Rong Yan, and Xiaowei Tang*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2193-2206

    https://doi.org/10.1007/s12555-023-0173-5

    Abstract

    Abstract : Bilateral teleoperation with force feedback allows the operators to apply their skills to accomplish challenging tasks safely. Most teleoperation bilateral systems are designed for single interaction scenarios and low-frequency force feedback, which limits their overall performance in complex interaction tasks. Furthermore, the use of passive controllers to ensure system stability can lead to further reductions in force transparency. This paper addresses the hybrid force feedback problem in complex interaction tasks with multiple stages, aiming at enhancing the practicality and robustness of teleoperation systems for complex interaction tasks, as well as reducing the force distortion caused by passive controllers. Firstly, an event-triggered hybrid force feedback architecture is proposed. Within this architecture, we introduce a two-channel fully transparent method with an explicit force controller (FT2-EFC), to enable model-free force tracking during both free motion and vibration contact stages. Besides, an adaptive impedance matching (AIM) algorithm is proposed to improve the physical interaction characteristics in the contact transient stage. Secondly, we present the operator passivity reference dual boundary energy tank (OPRDB-ET) method, which not only ensures the delay stability of the force architecture but also minimizes force distortion resulting from passive damping injection. Finally, experiments demonstrated that the proposed methods ensure the accurate tracking ability of hybrid forces in all stages of complicated interaction tasks and the slight force distortion under communication delay.

  • Regular PapersJuly 1, 2024

    Output Feedback Based Adaptive Continuous Sliding Mode Control for Mechanical Systems With Actuator Faults

    Tao Jiang, Yan Yan*, Shuang-He Yu, and Tie-Shan Li

    International Journal of Control, Automation, and Systems 2024; 22(7): 2207-2215

    https://doi.org/10.1007/s12555-023-0490-8

    Abstract

    Abstract : In this article, an adaptive continuous sliding mode control (SMC) scheme is presented for the trajectory tracking problem of mechanical systems with parameter uncertainties, external disturbances and actuator faults. The hyperbolic tangent function is widely used to replace the signum function in SMC to ensure that the robust term is continuous and to reduce chattering. Since such an approach is difficult for SMC schemes with adaptive gain to induce system stability through Lyapunov functions, we reconstruct the hyperbolic tangent function by taking both the adaptive control gain and sliding variables as inputs. The designed gain dynamics do not require a priori upper bound on lumped uncertainties, including parameter uncertainties, external disturbances and actuator faults, and ensure no overestimated gains. Besides, an adaptive dual-layer super-twisting (ADLST) observer is adopted to accurately estimate unmeasurable velocities, which achieves the synthesis of an adaptive sliding mode observer and the continuous SMC method with adaptive gain. It is proven through the Lyapunov function that all closedloop signals are ultimately bounded. Comparative simulations are conducted on a two-link rigid manipulator to demonstrate the effectiveness of the adopted observer and the proposed scheme.

  • Regular PapersJuly 1, 2024

    Expansion of the Workspace of Eye-in-hand Industrial Robots for Robust Hybrid Vision/force Control

    Bahar Ahmadi, Wen-Fang Xie*, and Ehsan Zakeri

    International Journal of Control, Automation, and Systems 2024; 22(7): 2216-2229

    https://doi.org/10.1007/s12555-022-0251-0

    Abstract

    Abstract : In this paper, a novel approach to workspace expansion for eye-in-hand industrial robots is presented to address the problem of the camera’s field-of-view (FOV) limitation in hybrid vision/force control. During the interaction with the workpiece, the camera and the workpiece are at a short distance from each other. Thus, the FOV is very small, which restricts the robot’s workspace. To handle this issue, instead of using only a feature object in conventional image-based visual servoing (IBVS), an array of objects is provided on the workpiece in a way that at least one object is entirely in the FOV. However, the conventional IBVS cannot be employed for hybrid vision/force control of such tasks. Thus, for this purpose, using a fuzzy inference system (FIS) and orthogonality principle, a novel hierarchical sliding surface is devised, and the continuous integral sliding mode controller (CISMC) is adopted, which leads to a robust and precise control method to fulfill the mentioned task. The stability of the proposed method is also proved. Experimental tests are conducted using an industrial robot on a workpiece whose results reveal the feasibility and effectiveness of the proposed approach. The results are also compared with traditional methods and show that the workspace expansion and control performance have been improved to a great extent.

  • Regular PapersJuly 1, 2024

    Partial Potential Energy Shaping Control of Torque-Driven Robot Manipulators in Joint Space

    Jesús Sandoval*, Rafael Kelly, Víctor Santibáñez, Javier Moreno-Valenzuela, and Luis Cervantes-Pérez

    International Journal of Control, Automation, and Systems 2024; 22(7): 2230-2241

    https://doi.org/10.1007/s12555-022-1196-z

    Abstract

    Abstract : The partial potential energy shaping control of fully actuated torque–driven robot manipulators in joint space is addressed in this paper. In contrast to the well-known potential energy shaping control of robot manipulators –which achieves global joint position regulation– here the term partial means to cancel out the natural potential energy at the joints selected by the user via the feedback control law. This formulation is useful when the robot joints are intended to track a desired time-varying trajectory that has joints with null potential energy. To the best of the authors’ knowledge, this is the first time that a formal analysis is presented on joint position tracking of robot manipulators by means of an adequate kinetic energy shaping plus total damping injection with partial potential energy shaping. The proposed controller is designed via an energy shaping plus damping injection approach, and the closed-loop system analysis is carried out via the Lyapunov’s theory and LaSalle’s theorem. Real-time experimental results on a manipulator arm model of two degrees of freedom illustrate the main results.

  • Regular PapersJuly 1, 2024

    Predefined-time Leader-following Consensus for Networked Euler-Lagrange Systems With External Disturbance

    Hui-Min Zhong, Tao Han*, Bo Xiao, Xi-Sheng Zhan, and Huaicheng Yan

    International Journal of Control, Automation, and Systems 2024; 22(7): 2242-2250

    https://doi.org/10.1007/s12555-023-0110-7

    Abstract

    Abstract : In this article, a predefined-time control framework is presented to accomplish the leader-following consensus for Euler-Lagrange (EL) systems, in which a dynamical leader is considered and only a subset of the followers can obtain the information from leader. In order to address the aforementioned problem, a predefinedtime control algorithm has been proposed. To be specific, a set of distributed estimators are firstly established to acquire the estimated states of the leader at a predefined time. Then, by applying the designed controller based on sliding surface control, the predefined-time leader-following consensus (PTLFC) problem has been addressed. Moreover, based on Lyapunov argument and input to state stability criterion, sufficient conditions for predefinedtime stability are derived. Finally, a large number of simulation examples are given to illustrate the validity of the main results.

  • Regular PapersJuly 1, 2024

    Nonlinear Disturbance Observer Incorporated Model Predictive Strategy for Wheeled Mobile Robot’s Trajectory Tracking Control

    Jiguang Peng, Hanzhen Xiao*, and Guanyu Lai

    International Journal of Control, Automation, and Systems 2024; 22(7): 2251-2262

    https://doi.org/10.1007/s12555-023-0207-z

    Abstract

    Abstract : In this paper, we discuss a nonlinear disturbance observer-based double closed-loop control system for managing a wheeled mobile robot (WMR) and achieving trajectory tracking control. The focus of our study is on the topic of trajectory tracking control for WMR in the presence of external disturbances. Our proposed control strategy addresses the two main issues of velocity constraint and external disturbances. Specifically, we employ a kinematic tracking error model to produce the constrained virtual velocity in the outer loop of a neural-dynamic optimizationbased model predictive control (MPC). Additionally, we create a nonlinear disturbance observer (NDO) based on the dynamic model to monitor external disturbances. To achieve accurate trajectory tracking for disturbances compensation, we utilize a robust controller. We confirm the stability of our proposed controller using the Lyapunov theory. Finally, two numerical simulation experiments demonstrate the effectiveness and reliability of our proposed controller.

  • Regular PapersJuly 1, 2024

    Interactive Robot Trajectory Planning With Augmented Reality for Non-expert Users

    Joosun Lee, Taeyhang Lim, and Wansoo Kim*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2263-2272

    https://doi.org/10.1007/s12555-023-0796-6

    Abstract

    Abstract : This paper presents a novel method for path selection by non-expert users in robot trajectory planning using augmented reality (AR). While AR has been used in robot control tasks, current approaches often require manual waypoint specification, limiting their effectiveness for non-expert users. In contrast, our study introduces an innovative AR-based method via a head-mounted display, designed to enhance human-robot interaction by making the process of selecting robotic paths more accessible to users without specialized expertise. The proposed method utilizes the RRT-Connect algorithm to automatically generate pathways from the initial to the goal position, offering choices of 1, 3, or 5 pathways, as well as 3 and 5 pathways with AR text guidance. This guidance provides contextual instructions within the AR environment, displaying the order of pathways from the fewest to the highest number of waypoints. Our findings demonstrate that optimizing the number of AR pathways can reduce user stress and improve operational skills. Path1 exhibited the fastest performance time but had the highest number of obstacle collisions. Methods with AR text guidance showed increased performance time compared to Path1. However, Path3 and Path5 achieved the best balance between performance time and collision avoidance. Qualitative analysis indicated that AR text displays demanded more effort from users. Path3 without AR text guidance was identified as the easiest method for operating the robot. Consequently, Path3 was deemed the most beneficial among the five methods. These results highlight the novelty of our method in enhancing the design of future human-robot interaction systems, focusing on improving efficiency, safety, and user experience for non-expert users using AR interfaces.

  • Regular PapersJuly 1, 2024

    Design and Modeling of a Two-wheeled Differential Drive Robot

    John Moritz*, Mishek Musa, and Uche Wejinya

    International Journal of Control, Automation, and Systems 2024; 22(7): 2273-2282

    https://doi.org/10.1007/s12555-023-0288-8

    Abstract

    Abstract : There are many existing publications on balancing two-wheeled, differential drive robot (TWDDR) covering dynamic modeling, kinematic modeling, path planning, control architecture design and/or simulations. However, there are few papers that cover all of these in a comprehensive manner that is approachable to beginner robotics researchers. This paper provides step-by-step details of the robotic design process including dynamic modeling, kinematic modeling, linearization, autonomous navigation, path planning, and stability control. A cascaded PID control architecture is presented that is capable of stabilizing the robot in less than 1 s with minimal steady-state error and performing large force and torque disturbance rejection. Additionally, a high-level path planning algorithm based on artificial potential fields is demonstrated.

  • Regular PapersJuly 1, 2024

    Exponential Synchronization of Stochastic Time-delayed Memristor-based Neural Networks via Pinning Impulsive Control

    Yao Cui and Pei Cheng*

    International Journal of Control, Automation, and Systems 2024; 22(7): 2283-2292

    https://doi.org/10.1007/s12555-022-1090-8

    Abstract

    Abstract : This paper investigates the exponential synchronization of stochastic time-delayed memristor-based neural networks (MBNNs) with using pinning impulsive control. Different from the traditional impulsive control schemes, a hybrid pinning impulsive control scheme is presented, and some sufficient conditions for exponential synchronization of system are established. Moreover, on the basis of the obtained results, the problem of delayed impulsive stabilization of stochastic time-delayed MBNN is studied. At last, an example is provided to demonstrate the validity of the obtained results.

  • Regular PapersJuly 1, 2024

    Robust Gradient Iterative Estimation Algorithm for ExpARX Models With Random Missing Outputs

    Chuanjiang Li, Wei Dai, Ya Gu*, and Yanfei Zhu

    International Journal of Control, Automation, and Systems 2024; 22(7): 2293-2300

    https://doi.org/10.1007/s12555-023-0555-8

    Abstract

    Abstract : This study presents a LookAhead-RAdam gradient iterative algorithm to identify ExpARX models with random missing outputs. The LookAhead-RAdam gradient iterative algorithm is used to optimize the step size of each element and adjust the direction to effectively update the ExpARX model parameter estimation through the estimated outputs. Compared to the classical gradient iterative algorithm, this study improves the estimation accuracy of the missing outputs and the parameter estimation convergence rate by introducing the LookAhead algorithm and RAdam algorithm. To validate the algorithm developed, a series of bench tests were conducted with computational experiments. Finally, the effectiveness of the proposed design approach is demonstrated by a simulation example.

  • Regular PapersJuly 1, 2024

    Method of Predicting Braking Intention Using LSTM-CNN-Attention With Hyperparameters Optimized by Genetic Algorithm

    Wei Yang*, Yu Huang, Kongming Jiang, Zhen Zhang, Ketong Zong, and Qin Ruan

    International Journal of Control, Automation, and Systems 2024; 22(7): 2301-2312

    https://doi.org/10.1007/s12555-021-1113-x

    Abstract

    Abstract : Prediction of a driver’s braking intention enables the advanced driver assistance system (ADAS) to intervene in the braking system as early as possible, which may shorten braking distance and improve driving safety. This paper proposes a novel deep learning model called LSTM-CNN-Attention that combines a long short-term memory (LSTM) neural network, convolutional neural network (CNN), and Attention mechanism for extracting spatiotemporal features of multi-sensor data to improve prediction accuracy. The proposed model inherits both temporal and spatial feature extraction abilities from LSTM and CNN. The LSTM-CNN-Attention model has a parallel architecture, which enhances the feature extraction ability of the model for multi-sensor time series data and improves the prediction accuracy of the driver’s braking intention before the braking action. Furthermore, a driving simulator is set up to sample driving data for training and evaluating the proposed method. According to the results of the experiment, the model obtains up to 3.16% higher accuracy than the baseline models such as LSTM, CNN, and bidirectional LTSM (Bi-LSTM). Additionally, the influence of sliding window size and prediction horizon on the performance of the method is investigated. A method of tuning hyperparameters using the genetic algorithm is presented. The results demonstrate that the prediction accuracy increases by about 2% after being optimized by GA.

  • Regular PapersJuly 1, 2024

    Abstract

    Abstract : This paper aims at the study of the general decay synchronization of state and spatial diffusion coupled delayed reaction-diffusion memristive neural networks (CDRDMNNs). At first, we present the general decay synchronization concept for the considered network based on ψ-type stability, then we go deeply into the establishment of general decay synchronization criterion of state CDRDMNNs by excogitating a proper controller and utilizing an opportune Lyapunov functional, thereby gain a sufficient condition for attaining general decay synchronization of state CDRDMNNs. Subsequently, we devote ourselves to investigating the general decay synchronization of spatial diffusion CDRDMNNs and derive an adequate condition for realizing the general decay synchronization of this type of network. Next, some sufficient conditions which ensure robust general decay synchronization of state CDRDMNNs and spatial diffusion CDRDMNNs with uncertain parameters are concluded by utilizing various types of inequality techniques. Ultimately, the efficacy of the acquired general decay synchronization results are certified via numerical simulations of two examples.

  • Regular PapersJuly 1, 2024

    Application of a Hybrid Improved Particle Swarm Algorithm for Prediction of Cutting Energy Consumption in CNC Machine Tools

    Jidong Du, Yan Wang*, and Zhicheng Ji

    International Journal of Control, Automation, and Systems 2024; 22(7): 2327-2340

    https://doi.org/10.1007/s12555-022-0784-2

    Abstract

    Abstract : Estimation and analysis of energy consumption for machine tool is the basis of energy efficiency improvement. To improve the accuracy of ELM algorithm in CNC machine tool energy consumption prediction, a prediction method based on an improved particle swarm optimization (CAPSO) algorithm and an extreme learning machine (ELM) is proposed. The contribution of the algorithm includes the following three aspects. First, sobol sequence is used to initialize the PSO population to make distribution of initial population more even in solution space. Second, the center wanders and boundary neighborhood updates strategy are used to improve the population quality and convergence rate of PSO. Then, to avoid the optimal local solution, the adaptive inertia weight is introduced to achieve the stochastic perturbation of the population. The performance of the algorithm is tested by ten benchmark function, indicating that the CAPSO ensures the search accuracy and improves the algorithm’s convergence rate. Finally, the CAPSO algorithm is used to optimize the weights and thresholds of an ELM, and the CAPSO-ELM cutting energy consumption prediction model is established. Case analysis and comparative experiments show that the stability, prediction accuracy and generalization ability of CAPSO-ELM model are better than those of other models.

IJCAS
July 2024

Vol. 22, No. 7, pp. 2055~2340

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