Current Issue
Vol. 23, No. 3, March 2025
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Regular PapersMarch 1, 2025
Regulation of Feedforward Nonlinear Systems Under Unknown Time-varying Multiple Delays via Dynamic Gain Control
Sang-Young Oh and Ho-Lim Choi*
International Journal of Control, Automation, and Systems 2025; 23(3): 683-691AbstractAbstract : We consider a state feedback regulation problem for nonlinear systems with multiple unknown timevarying delays in the input. The considered perturbed nonlinearity has feedforward terms and unknown growth rate. To deal with unknown multiple delays, we propose a newly designed adaptive state feedback controller by utilizing the dynamic gain. We also describe how this system can be globally regulated using our control method and Lyapunov stability analysis. The effectiveness of our method is clearly illustrated via numerical and practical examples under known time-varying multiple delays.
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Regular PapersMarch 1, 2025
Robust Delay-dependent Stability of Nonlinear Stochastic Systems Subject to Passivity Performance
Chein-Chung Sun, Ping-Tzan Huang*, Cheung-Chieh Ku, and Kuan-Wei Huang
International Journal of Control, Automation, and Systems 2025; 23(3): 692-703AbstractAbstract : The delay-dependent stability issue of nonlinear stochastic systems with external disturbance is investigated in this paper subject to passivity performance. Based on the Takagi-Sugeno (T-S) fuzzy model, the Itô formula and Lyapunov function are directly applied to discuss the stability issue. And, some perturbations are considered to represent the uncertainty for discussing the robustness. Moreover, the interval time-varying case represents the time delay effect on the system. A novel Lyapunov function is proposed to develop the stability criterion with the composing fuzzy positive definite matrix for reducing conservatism. Furthermore, a free-matrix-based inequality is employed to introduce some variables for increasing the freedom of calculation. Based on the proposed criterion, the less conservative delay-dependent stability criterion is applied to design a fuzzy controller such that the nonlinear stochastic system is robust asymptotically stable and passive in the mean square. Finally, two numerical simulations are provided to demonstrate the effectiveness of the proposed design method.
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Regular PapersMarch 1, 2025
An Adaptive Fault-tolerant Control Method for Markovian Jump Systems With Actuator Fault, Dead-zone, and External Disturbance
Hai Xuan Le, Van-Tinh Nguyen*, Linh Ngoc Nguyen, Hang Thanh Tran, Duy Duc Pham, and Dang Ngochai
International Journal of Control, Automation, and Systems 2025; 23(3): 704-713AbstractAbstract : This paper proposes an adaptive fault-tolerant control method for Markovian jump systems in the presence of actuator fault, unknown dead zone, and external disturbance. There is no prior knowledge of the exact model of the actuator fault. The uncertainty due to the actuator fault and unknown dead zone is tackled by the adaptive rules in the proposed control method. The actuator fault is assumed to be the partial loss of effectiveness. The stochastic stability of the entire system is assured through coupled linear matrix inequalities (LMIs) despite no prior knowledge of actuator fault, dead zone, and external disturbance. The simulation results have validated the merit and efficiency of this proposed control method.
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Regular PapersMarch 1, 2025
A Model-tuning Approach to Switching-type Dynamic Quantizer Design for Nonlinear Systems
Yugo Ogio*, Yuki Minami, and Masato Ishikawa
International Journal of Control, Automation, and Systems 2025; 23(3): 714-724AbstractAbstract : This paper focuses on designing discrete-valued input systems using dynamic quantizers, which convert continuous-valued signals into discrete-valued ones. Although there are many studies on the optimal design of dynamic quantizers, there are some unresolved problems. This study focuses on one of the unresolved problems: the design of a switching-type discrete-time dynamic quantizer for continuous-time nonlinear systems. In this paper, we first reduced the quantizer design problem to a selection problem of continuous-time linear models for a given nonlinear system. We formulate the selection of continuous-time linear models as an optimization problem. Then, we evaluated this approach via simulations of the swing-up problem for a cart-type inverted pendulum. Finally, we verify stability under different conditions and compare our proposed method and the direct search method for quantizers.
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Regular PapersMarch 1, 2025
Fully Distributed Leader-follower Event-triggered Control for TVMASs Under Undirected/Directed Graph
Lina Xia, Qing Li, and Ruizhuo Song*
International Journal of Control, Automation, and Systems 2025; 23(3): 725-736AbstractAbstract : The paper systematically studies the leader-follower (LF) problem in time-varying multi-agent systems (TVMASs) on undirected/directed graphs by a distributed/fully distributed event-triggered protocol. A general form of the event-triggered strategy is investigated to ensure state consensus among agents on an undirected and connected graph, which is extended to a directed graph containing a spanning tree. Then, two adaptive time-varying event-triggered strategies are provided to solve the LF problem on undirected and directed graphs such that the Laplacian matrix in design can be relaxed. A triggering condition and four novel event-triggered functions that involve dynamic parameters are designed under no Zeno behavior. Finally, the availability of the obtained systematic results is shown by a simulation example.
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Regular PapersMarch 1, 2025
A Robust Tube-based MPC Strategy With the Enhanced Memory State Feedback for Uncertain Constrainted Linear Systems With Time Delays
Zhuoer An, Xinghua Liu*, Gaoxi Xiao, Yu Kang, and Peng Wang
International Journal of Control, Automation, and Systems 2025; 23(3): 737-747AbstractAbstract : In this article, considering the general existence of the time delay phenomenon that affects the system stability in uncertain constrained discrete linear system, we propose an optimal robust tube-based model predictive control (RTMPC) strategy to simultaneously deal with the external disturbances and time delays. Firstly, the robust control constraints for a nominal linear system with time delays are designed to address the uncertainties in the robust MPC algorithm. Compared with classical robust MPC methods, these constraints can limit the state of the nominal system to a small range, thereby reducing the system conservatism and enhancing robustness to system uncertainty. In addition, due to the consideration of time delay states in the proposed robust controller, the system has memory ability during optimization calculation, which can improve system control performance to a certain extent. Finally, the effectiveness of the proposed RTMPC strategy are demonstrated through the comparative simulations.
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Regular PapersMarch 1, 2025
Low-rank Alternating Direction Doubling Algorithm for Solving Large-scale Continuous Time Algebraic Riccati Equations
Juan Zhang* and Wenlu Xun
International Journal of Control, Automation, and Systems 2025; 23(3): 748-756AbstractAbstract : In this paper, we propose an effective low-rank alternating direction doubling algorithm (R-ADDA) for computing numerical low-rank solutions of large-scale sparse continuous-time algebraic Riccati matrix equations. Our algorithm represents a further extension of the alternating direction doubling algorithm, utilizing the lowrank property of matrices. It is only required to compute one recursion and may apply the associated low-rank structures, solving large-scale problems efficiently. The low-rank formula can save storage space and computational complexity. Finally, we offer theoretical analysis and numerical experiments to illustrate the effectiveness of the derived algorithm.
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Regular PapersMarch 1, 2025
Robust Model Predictive Control for Uncertain Impulsive Positive System
Donglin Shi, Jun Ai, and Yuchang Feng*
International Journal of Control, Automation, and Systems 2025; 23(3): 757-766AbstractAbstract : This study delves into a robust model predictive control method for impulsive positive system, incorporating control input/state constraints and interval uncertain. Initially, a state feedback controller is devised, and sufficient conditions for ensuring positivity and stability of the closed-loop impulsive positive system with interval uncertain are obtained utilizing the linear copositive Lyapunov function and the linear cost function. Subsequently, linear programming techniques are applied to solve the optimization problem, yielding optimal control inputs. This designed control strategy ensures the system’s positivity and stability while meeting control input/state constraints. Lastly, the validity of the approach is proved using numerical simulation examples.
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Regular PapersMarch 1, 2025
Fixed-time Formation Control for Leader-following Multi-agent Systems With Disturbances and Nonlinear Function Under Directed Topology
Zhangyi Zu, Jie Wu*, Xisheng Zhan, Bo Wu, and Lingli Cheng
International Journal of Control, Automation, and Systems 2025; 23(3): 767-776AbstractAbstract : This paper presents a solution for the fixed-time time-varying formation tracking problem in multi-agent systems that incorporate nonlinear function and external disturbances under a directed communication topology. First, the investigated novel fixed-time observer allows every follower to estimate the leader’s state. The subsequent design of a novel controller is focused on the goal of facilitating not just the expected formation and successful pursuit of a leader within a fixed time. This indicates that the limit of the settling time is not contingent upon the initial value. In addition, further improvements have been made to the proposed protocol so that it can be used more widely in practice. Ultimately, two examples are utilized to substantiate the efficacy of the aforementioned hypothesis.
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Regular PapersMarch 1, 2025
Data-driven Detection of Hot Spots in Photovoltaic Modules Using Information Fusion
Hui Yi*, Jianfei Liu, Deshan Zeng, Chen Yang, and Hongtian Chen
International Journal of Control, Automation, and Systems 2025; 23(3): 777-787AbstractAbstract : Hot spots are common defects in photovoltaic (PV) modules that can lead to performance degradation and even pose a fire hazard. This study proposes an online detection methodology for hot spots within a data-driven framework. The modeling of PV modules under normal conditions relies on the integration of two-dimensional information. The first dimension pertains to the correlation among measured variables across multiple tests, while the second dimension captures the local nonlinearity among past, present, and future measurements from PV modules. By combining these two dimensions of information, accurate modeling of PV modules can be achieved in a data-driven manner. Based on this model, the performance-oriented detection of hot spots in PV modules is formulated in detail. The proposed approach is then applied to both darkroom and outdoor PV systems, with a total of 23 tests and comparisons conducted. The results of these tests and comparisons convincingly demonstrate the validity and superiority of the proposed method.
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Regular PapersMarch 1, 2025
On the Nonlinear Control of a Class of Cruise Missiles
Subbareddy Chitta and Ramakalyan Ayyagari*
International Journal of Control, Automation, and Systems 2025; 23(3): 788-797AbstractAbstract : This paper focuses on enhancing the design of control systems for nonlinear missile models using the feedback linearization (FL) technique. First, the missile model is transformed by employing FL into a quasilinearized fourth order model, permitting the design of well-known linear state feedback control strategies. Several challenges encountered in this process are discussed and the most practical transformation is chosen to arrive at the implementation of the quasi-linearized model in the inner loop around the plant. Secondly, for the outer loop, an optimal control policy of the form u = Kx is devised using the standard linear quadratic regulator (LQR) framework, wherein it is noticed that the choice of the weighting matrices Q (positive semi-definite) and R (positive definite) is of paramount importance in obtaining the state feedback matrix K. Here an attempt is made to place all the four poles at the right locations via the Q and R matrices. This is in contrast to the popular design of considering only a pair of dominant poles and ignoring the effects of the other two poles. The state feedback control u = Kx in the outer loop is converted to a nonlinear control in the inner loop via the transformations employed in FL. Thus, the nonlinear plant remains intact. Next, to tackle the well-known difficult task of arriving at the right set of Q and R matrices, an innovative iterative procedure is proposed to quickly converge to suitable matrices. For the fourth order system, for comparison purposes, the standard state feedback (SSF) controller is also designed. Lastly, the performance of the nonlinear control system designed is compared to that of the linearized missile model controlled using classical techniques, as is mostly found in the literature. The effectiveness and advantages of employing FL techniques are demonstrated through extensive analysis and simulation studies, highlighting the superiority and ease of design of the proposed LQR controller.
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Regular PapersMarch 1, 2025
Design of an Inflatable Exhaust Valve to Improve Bandwidth of Inflatable Actuators: A Feasibility Study With a Soft Knee Wearable Robot
Junghoon Park, Youngjin Na*, and Jung Kim*
International Journal of Control, Automation, and Systems 2025; 23(3): 798-809AbstractAbstract : In this study, we designed an inflatable soft actuator with a novel pneumatic inflatable exhaust valve to reduce exhausting time. The soft wearable robots using inflatable actuators had limitations in joint movement during exhaus phase due to residual air remaining in the actuators since the exhaust time was long. We proposed the novel pneumatic inflatable exhaust valve by utilizing the pneumatic power transmission to block larger orifices compared with commercial pneumatic valves. Two inflatable layers of the proposed valve were installed at the top and bottom of the actuator layer to cover the large exhaust area. Our actuator’s deflation time was 0.13 seconds using the proposed valves and it was 3.2 times faster than using only a commercial solenoid valve. The -3 dB bandwidth of exhausting air was 4.2 Hz for our actuator. Moreover, the actuator bandwidth was 3.4 Hz from the dynamic response experiment, which was sufficient to cover the human walking frequency. Lastly, we validated our actuator to assist knee movements for ground walking and stair ascending through the developed fully wearable soft knee robot.
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Regular PapersMarch 1, 2025
An Extended State Observer-based on the Terminal Sliding Mode Control for 6-DOF Manipulator Against Lumped Uncertainties
Duc Thien Tran, Hai Ninh Tong, and Kyoung Kwan Ahn*
International Journal of Control, Automation, and Systems 2025; 23(3): 810-823AbstractAbstract : This paper presents an extended state observer (ESO) based on the terminal sliding mode control (TSMC) for a 6-degree-of-freedom (DOF) manipulator under the presence of dynamics error, unknown friction force, external disturbance, and loss-of-effectiveness on actuators. The proposed control strategy is constructed by the TSMC and ESO to eliminate the lumped uncertainties and enhance the tracking error performance. Initially, the tracking trajectory control is handled by the TSMC, which inherits the advantages of the conventional sliding mode control (SMC) and gives the system state errors approach the zero point in finite-time convergence and robustness against nonlinearity. Next, a linear ESO is investigated to estimate the lumped uncertainties to improve the effectiveness and descend the high oscillatory on the TSMC. In addition, the stability analysis of the control system is proven by the Lyapunov stability theorem. Finally, numerical simulations are established on MATLAB Simulink. To demonstrate its effectiveness and precision, the proposed control results are compared with alternative controllers via performance indices.
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Regular PapersMarch 1, 2025
Formation Control of Multiple Rotorcraft Unmanned Aerial Vehicles With Nonlinear Flight Dynamics
Jun-Young An and Chang-Joo Kim*
International Journal of Control, Automation, and Systems 2025; 23(3): 824-839AbstractAbstract : This paper presents two novel formation control methods for large-scale rotary-wing unmanned aerial vehicles (RUAVs), addressing the challenges posed by nonlinear flight dynamics. The virtual tigid-body kinematicsbased formation control method (VRKFCM) models the RUAVs as point particles relative to the leader, while the relative trajectory-based formation control method (RTFCM) generates follower trajectories using spline interpolation based on the leader’s motion. Both methods integrate incremental backstepping control to ensure precise trajectory tracking. Simulations of complex maneuvers, including pirouette and helical turns, demonstrate the effectiveness of these methods in maintaining formation stability under challenging flight conditions. This study contributes to the field by incorporating high-fidelity nonlinear dynamics into formation control, offering a more realistic approach for large-scale RUAV operations.
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Regular PapersMarch 1, 2025
Dynamic Modeling of Magnetorheological Damper Based Three-link Model for Human Lower Limb
Akhila Bhat, Vidya S. Rao*, and Jayalakshmi N. S.
International Journal of Control, Automation, and Systems 2025; 23(3): 840-851AbstractAbstract : Orthotic devices are very crucial in supporting the individuals with movement impairment and they help ease the burden of treatment and rehabilitation. The research is devoted to the development and result analysis of novel smart orthotic model used along with magneto-rheological (MR) damper. This is due to the fact that MR damper has a unique characteristic of mechanically adapting itself in real time by changing stiffness and damping through an applied magnetic field to achieve control and adaptation. The model design procedure comprises of the development of MR damper based exoskeleton with an actual human lower limb, to maintain flexibility and improve the efficiency of affected limb. Main focus of this research work is to improve the complaince of the affected lower limb joint as compared with healthier one. Extensive evaluations and validation tests were performed in order to test its efficiency. These assessments contained the simulated studies through Matlab software. Preliminary results showcase the MR damper-based orthotic device’s ability to dynamically adjust its stiffness to optimize support while allowing controlled movement. Additionally, in comparison with 2 link modeling, the 3-link model has shown promising outcomes which could further be used for advanced control algorithms. This research work contributes to the advancement of orthotic technology by leveraging MR damper capabilities, offering a novel approach to personalized and adaptable support for individuals with movement impairments.
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Regular PapersMarch 1, 2025
Trajectory Tracking Control Design for Single-link Flexible Manipulator: An Observer Based Integral Sliding Mode Approach
Atul Sharma* and S. Janardhanan
International Journal of Control, Automation, and Systems 2025; 23(3): 852-859AbstractAbstract : This paper introduces a novel robust trajectory tracking control algorithm for a single-link flexible manipulator that uses a state observer-based integral sliding mode approach. The inherent flexibility present in the manipulator link introduces challenges in achieving precise trajectory tracking due to dynamic complexities and vibration at the tip. In order to overcome these difficulties, an integral sliding mode control law is designed that provides resilience against external disruptions and model uncertainties. A state observer complements the proposed control approach, ensuring the precise implementation of the proposed control algorithm with output measurement alone. The proposed control’s efficacy is established through numerical simulations and experimental verification.
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Regular PapersMarch 1, 2025
Reduced-order Observer Based Trajectory Tracking Control of Quadrotor Subject to Noises and Disturbances
Nigar Ahmed, Meng Joo Er*, and Syed Awais Ali Shah
International Journal of Control, Automation, and Systems 2025; 23(3): 860-868AbstractAbstract : This paper presents a control technique to achieve trajectory tracking for a quadrotor subject to internal noises and external disturbance. The methodology involves designing a nonlinear disturbance observer to estimate and reject six different types of disturbances within the quadrotor model, followed by employing state transformation using tracking error and backstepping state space variables to formulate a robust control algorithm. In addition, adaptive laws are obtained using Lyapunov criteria to achieve online control gain tuning. Furthermore, a state observer technique utilizing a reduced-order observer is designed to estimate only the rotational and translational rates using measurable outputs. Finally, the control algorithm is finalized by using the estimated states and disturbances, and adaptive laws. The developed robust adaptive control technique relies solely on desired trajectory information and measurable rotational and translational outputs, thereby reducing the number of onboard sensors required for measurements of rotational and translational rates. The stability analysis is carried out using Lyapunov theory proving asymptotic convergence to the neighbourhood of origin. Simulations are performed on a DJI F450 quadrotor, demonstrating effectiveness and tracking performance of controller for two desired reference trajectories.
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Regular PapersMarch 1, 2025
Design and Admittance Control of a Linear Single-spring Hydraulic Series Elastic Actuator
Shengyu Lu, Sicheng Xie, Jingyuan Li, and Liang Gao*
International Journal of Control, Automation, and Systems 2025; 23(3): 869-881AbstractAbstract : Series elastic actuators (SEAs) offer some benefits, such as shock absorption, power amplification, and buffering capabilities. Among them, hydraulic SEAs have added advantages related to high power density, thereby improving the performance of robotic joints. This paper proposes an innovative bi-directional flexibility singlespring mechanism, serving as a foundational element of a linear single-spring hydraulic SEA (SH-SEA). A highperformance admittance controller for the linear SH-SEA is also developed. The advantages of the new singlespring mechanism are thoroughly investigated. After comparison, the initial size of the spring in the single-spring mechanism is less than half the initial size of all springs in the conventional double-spring mechanism, or the energy storage capacity of the single-spring mechanism is more than twice that of the double-spring mechanism. So, the SH-SEA is inherently compact and has better energy efficiency. The proposed admittance controller self-optimizes compensation parameters for the hydraulic cylinder’s asymmetry and the expected position’s amplitude attenuation. It also compensates for time delay of the system. Experimental results demonstrate the effectiveness of the proposed admittance controller in accurately tracking both the position and stiffness of the linear SH-SEA.
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Regular PapersMarch 1, 2025
Robust Continuous Sliding Mode Torque Tracking Control for Compliant Actuators With Prescribed Performance
Xiaoou Lin, Fuxin Du*, Jianping Song, Changwei Yin, Yang Zhang, and Yibin Li
International Journal of Control, Automation, and Systems 2025; 23(3): 882-895AbstractAbstract : The development of compliant actuators has garnered tremendous interest in recent years, particularly for their ability to simplify a torque control problem into a deformation position control problem. In order to ameliorate torque control of compliant actuators subject to unknown external disturbances and model parameter uncertainties, a robust composite control strategy is proposed in this article. Firstly, an extended state observer is employed to estimate the lumped disturbance, and a continuous control law is achieved by adopting continuous sliding mode control. Then, the switching gain is only required to exceed the upper bound of the estimation error. Furthermore, by introducing prescribed performance control technology, a novel sliding surface based on transformed error and disturbance estimation is designed, which guarantees rapid global convergence, superior transient performance, strong robustness, and minimal chattering. The closed-loop system stability is rigorously proven using the Lyapunov method. Finally, the simulation and experimental results validate the effectiveness of the proposed control strategy.
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Regular PapersMarch 1, 2025
Enhanced Hydraulic Excavator Control via Semi-automatic Grading Control Using Reinforcement Learning
Youngbum Kim and Jinwhan Kim*
International Journal of Control, Automation, and Systems 2025; 23(3): 896-906AbstractAbstract : This paper introduces a novel control approach for automated excavators combining model-based and learning-based techniques to enhance control accuracy. The feedback linearization technique is employed based on error dynamics in designing boom and bucket velocity controllers incorporating the driver’s manual arm control. Additionally, supervised learning is used to approximate inverse hydraulic actuation system and to compute joy stick control inputs corresponding to the desired control velocity. To further refine control precision reinforcement learning is used to optimize the driver’s manual arm manipulation within a given cycle time. The performance of the proposed methodology is demonstrated through simulations on a 30-ton excavator and compared with results based on model-based techniques.
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Regular PapersMarch 1, 2025
Genetic Algorithm Based Takagi-Sugeno Fuzzy Modelling of a Mecanum Wheeled Mobile Robot
Muhammad Qomaruz Zaman and Hsiu-Ming Wu*
International Journal of Control, Automation, and Systems 2025; 23(3): 907-919AbstractAbstract : This study introduces a Takagi-Sugeno (T-S) fuzzy modeling framework for kinematic modeling of mecanum wheeled mobile robot (MWMR). T-S fuzzy systems are particularly effective in capturing complex nonlinear dynamics and unmodeled subsystems inherent to MWMR architectures. Optimization of parameters within the T-S structure is achieved through a genetic algorithm (GA), enabling precise alignment between the T-S derived model and physical system behavior. Notably, the proposed methodology achieves convergence to optimal T-S model within 200 generations of the GA, without necessitating an explicit analytical formulation of the complete MWMR dynamics. Validation experiments reveal the optimized T-S model achieves 0.015 m/s a mean squared error (MSE) difference relative to empirical velocity profiles from the MWMR platform. Rigorous numerical assessment demonstrates the formulated T-S model achieves exceptional dynamic congruence with the physical MWMR platform, manifesting peak velocity discrepancies of 57×10−4 m/s accompanied by standard deviations of 0.027 m/s across experimental trials. Comparative evaluation against conventional probabilistic modeling techniques highlights superior predictive accuracy and dynamic fidelity of the proposed T-S framework. Observed results substantiate the model’s capacity to replicate nonlinear kinematic interactions and transient velocity characteristics under experimentally validated boundary conditions, corroborating theoretical expectations through empirical system identification.
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Regular PapersMarch 1, 2025
NN-augmented EKF for Robust Orientation Estimation Based on MARG Sensors
Akos Odry*, Istvan Kecskes, Richard Pesti, Dominik Csik, Massimo Stefanoni, Jozsef Sarosi, and Peter Sarcevic
International Journal of Control, Automation, and Systems 2025; 23(3): 920-934AbstractAbstract : Magnetic, angular rate, and gravity (MARG) sensor-based orientation estimation is commonly implemented using extended Kalman filter (EKF) frameworks, where robustness against dynamic motions and magnetic disturbances is ensured through online EKF covariance updates. This paper proposes an alternative solution involving a neural network (NN) with an appropriate topology, which is trained to provide MARG correction signals to the EKF, thereby delivering disturbance-suppressed measurements for improved orientation estimation. First, the EKF-based orientation estimation is revisited, and the main sources of error are highlighted. Then, a universal laboratory framework is introduced, which performs various motions with a calibrated UR5 cobot and records the raw measurements from a MARG sensor attached to its end-effector, along with ground truth pose data. Using a comprehensive database consisting of 16 different scenarios, the derivation of target signals for error-corrected MARG data is presented. Next, three shallow NN architectures—feed forward NN (FFNN), cascade forward NN (CFNN), and focused time-delay NN (FTDNN)—are trained for these targets, and their performances are evaluated using Pearson’s correlation metrics as a function of the number of hidden neurons and input channel combinations. Finally, each NN-EKF combination is assessed, and it is found that the FFNN offers the most suitable topology in terms of both performance and computational cost. The proposed FFNN-EKF approach enhances orientation estimation quality by a significant 44.5% based on the mean squared quaternion error metrics, even in highly disturbed environments. The performance of the FFNN-EKF is also compared to other common methods, demonstrating that the proposed approach outperforms the benchmark filters.
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Regular PapersMarch 1, 2025
Model-free Adaptive Iterative Learning Control for Nonlinear Systems With Time-varying Constraints
Yan Wei, Yong-Qi Zhang, Zi-Yuan Dong, Lin-Lin Ou*, and Xin-Yi Yu*
International Journal of Control, Automation, and Systems 2025; 23(3): 935-944AbstractAbstract : In this paper, an approach is designed to tackle the complex challenges of modeling unknown systems. This approach addresses the difficulty of relying on accurate modeling information when ensuring the security of a dynamics system. A model-free adaptive iterative learning safety control approach is designed based on the iterative control barrier function. Firstly, the dynamic model of the unknown system is discretized to create a discrete-time model. This transformation incorporates nonlinear model uncertainty by employing iterative dynamic linearization. Simultaneously, the uncertainty is estimated and compensated by radial basis function neural networks (RBFNNs). To ensure safety under time-varying constraints, a model-free adaptive iterative learning method with discrete control barrier function is designed based on the designed dynamic iterative model. Ultimately, the validity of the proposed approach is verified on the Franka-Panda robot platform.
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Regular PapersMarch 1, 2025
Distributed Finite-time Adaptive Fuzzy Event-triggered Formation Scheme for Multiple QUAVs Under Time-varying Asymmetric State Constraints
Changhui Wang*, Yihao Wang, and Mei Liang*
International Journal of Control, Automation, and Systems 2025; 23(3): 945-959AbstractAbstract : This article investigates the event-triggered adaptive fuzzy finite-time formation of the multiple quadrotor unmanned aerial vehicles (QUAVs) under time-varying asymmetric state constraints and disturbances. Firstly, the unknown continuous nonlinearities of the QUAVs are approximated by the fuzzy logic systems (FLSs), and the distributed estimators with adaptive parameters are constructed to estimate and compensate the composite disturbances. Secondly, the command filters are introduced into the controller design process to eliminate complexity explosion problem, and the errors compensation mechanism based on communication network is introduced to compensate the filtering errors. Thirdly, by building the communication mechanism between the QUAVs and the virtual leader, the event-triggered finite-time tracking scheme is established to reduce unnecessary transmission of network resources. The stability of the proposed finite-time distributed formation scheme is analyzed, and it is verified that all the signals of QUAVs are bounded without exceeding the preset time-varying state constraints. The event trigger interval has a positive lower bound and the tracking errors converge to a small origin neighborhood in a finite time. Finally, simulation results are carried out to verify the superiority and effectiveness of the presented formation algorithm.
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Regular PapersMarch 1, 2025
Composite Anti-disturbance Tracking Control for the Conversion Mode of Tilt-rotor Aircraft via Switched Fuzzy Modeling
Wen Li, Shuang Shi, Mou Chen*, Shuyi Shao, and Qingxian Wu
International Journal of Control, Automation, and Systems 2025; 23(3): 960-972AbstractAbstract : The modeling and control problems for the conversion mode of tilt-rotor aircraft are discussed with a switched Takagi-Sugeno (T-S) fuzzy modeling method and an H∞ anti-disturbance tracking control design technique. First, a more general nonlinear motion equation of the conversion mode is deduced by taking the rotor effect into consideration. Second, a switched T-S fuzzy model with an exosystem is adopted to precisely approximate the nonlinear model with an uncontrolled tilting angle. Furthermore, the mast angle is chosen as the premise variable to improve the model accuracy. On this foundation, the conversion mode control problem is transformed to a state tracking control design of the obtained switched T-S fuzzy system. Third, in order to improve the tracking performance, an H∞ anti-disturbance control scheme is proposed, which includes the switched T-S fuzzy controller and the disturbance observer. In this way, both internal and external disturbances can be attenuated. Finally, the simulation result with respect to the XV-15 tilt-rotor aircraft is provided to illustrate the effectiveness and merits of the developed modeling and control scheme.
Vol. 23, No. 3, pp. 683~972
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Editorial: The 22nd International Conference on Control, Automation, and Systems (ICCAS 2022)
Hyo-Sung Ahn
International Journal of Control, Automation, and Systems 2023; 21(8): 2429-2429 -
A Review on Intelligent Scheduling and Optimization for Flexible Job Shop
Bin Jiang*, Yajie Ma, Lijun Chen, Binda Huang, Yuying Huang, and Li Guan
International Journal of Control, Automation, and Systems 2023; 21(10): 3127-3150
