Article
Engineering, Mechanical
Mohammad Al Janaideh, Almuatazbellah M. Boker, Micky Rakotondrabe
Summary: This study proposes a new output-feedback tracking control scheme for a class of precision motion systems with unknown hysteresis nonlinearity and linear dynamics. The effectiveness of the method is demonstrated through simulation and experimental results.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Information Systems
Shunjiang Wang, Xiurong Ou, Dianyang Li, Hongzhe Wang, Guoqiang Zhu
Summary: An output feedback adaptive quantized control protocol based on k-filter observer is proposed for a Multi-machine excitation system with transmission delays. The protocol constructs k-filter observers to estimate unmeasured states and compensate errors and nonlinearity, and uses a time-delay function approximator to deal with transmission delays. By initialization technique, small tracking error is achieved, and the control signal is quantized and transmitted to implement the system on computer. Experimental results show the effectiveness of the proposed protocol.
Article
Computer Science, Theory & Methods
Xingling Shao, Haonan Si, Wendong Zhang
Summary: This paper investigates an improved fuzzy wavelet neural control scheme for MEMS gyroscope, using a hysteresis quantizer (HQ) and modified prescribed performance control (MPPC) to achieve better output tracking and uncertainty identification.
FUZZY SETS AND SYSTEMS
(2021)
Article
Mathematics, Applied
Xiao-Heng Chang, Xue Jin
Summary: This paper investigates the observer-based quantized output feedback control for a kind of nonlinear discrete-time systems described by a Takagi-Sugeno (T-S) fuzzy model. An effective matrix inequality decoupling method is presented to handle the design of the controller, observer, and dynamic parameters of quantizers, showing that the design conditions can be synthesized synchronously. The resulting design ensures that the quantized closed-loop system meets the prescribed H-infinity performance, demonstrated by a mechanical motion system.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Automation & Control Systems
Xiaozhe Ju, Yushi Jiang, Liang Jing, Peng Liu
Summary: This paper addresses the quantized control problem for a heavy-lift launch vehicle (HLV) under actuator faults and rate gyro malfunctions. A predefined-time observer (PTO) is designed to reconstruct the immeasurable time derivative of attitude tracking errors with a precisely predefined settling time. A quantized controller is then developed using the reconstructed state to render attitude tracking errors within a small neighborhood of the origin within a predefined time interval, while accounting for actuator faults. The controller incorporates an unswitched singularity-avoidance layer, a hysteresis quantizer, and predefined settling time, offering advantages over existing quantized predefined-time controllers.
Article
Automation & Control Systems
Jing Wu, Wei Sun, Shun-Feng Su, Yuqiang Wu
Summary: This study introduces an adaptive quantized control scheme for uncertain strict-feedback nonlinear systems with unknown control directions. By combining backstepping technique and Lyapunov stability theory, a systematic analysis method is designed to overcome obstacles related to quantized input signals and unknown control directions. The effectiveness and feasibility of the control scheme are verified through simulation examples, demonstrating the boundedness of all signals and convergence of tracking error to a small domain of origin.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Marine
Hong-Du Wang, Yun-Xiang Zhai, Umer Hameed Shah, Mansour Karkoub, Ming Li
Summary: In this paper, an adaptive fuzzy control design problem is investigated for an underwater vehicle manipulator system based on a fuzzy performance observer and fuzzy disturbance observer. A novel pre-deadzone compensator is proposed to mitigate the dead-zone and hysteresis effects. Fuzzy logic systems with online adaptations are utilized to evaluate the unknown components of the system, and an H infinity fuzzy control technique is developed to reduce errors in estimating external disturbances. The stability and tracking performance of the closed-loop system are analyzed using Lyapunov stability theory, showing that all signals are uniformly ultimately bounded. Simulations demonstrate the effectiveness of the proposed control scheme in addressing the tracking control problem of the underwater vehicle manipulator system.
Article
Automation & Control Systems
Xingling Shao, Xiaohui Yue, Wendong Zhang
Summary: This article addresses the fuzzy-quantized elliptical target encircling control of quadrotors with arbitrary-time convergence, consisting of translational and rotational designs. The proposed approach includes an arbitrary-time elliptical guidance rule for translational control and a fuzzy-quantized attitude regulation protocol for rotational control. The stability of the overall system is demonstrated and the efficacy of the approach is verified through simulations and experiments.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Su Yunzhe, Yajun Yang, Xuerong Yang
Summary: This paper addresses the adaptive attitude tracking control with limited communication to actuators. A rotation matrix is used rather than a quaternion to describe the attitude, and its stability is proved using Morse-Lyapunov function. Two different quantizers, logarithmic quantizer and hysteresis quantizer, are employed to quantize the control torque signal to meet the restricted communication requirement. Two robust adaptive control techniques, indirect and direct, are proposed to handle the impacts of quantization error and external disturbances. The proposed control schemes guarantee the global boundedness of all signals in the closed-loop system, enabling the attitude tracking error to converge to an ultimately bounded region. Numerical simulations are conducted to demonstrate the performance of the proposed controllers.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2023)
Article
Engineering, Mechanical
Zhuangbi Lin, Zhi Liu, Yun Zhang, C. L. Philip Chen
Summary: An indirect adaptive consensus control method is proposed for multi-agent systems with unknown hysteresis states and input. The method includes an inverse adaptive compensated method to eliminate the influence of unknown input hysteresis and two adaptive laws to address the problem of state hysteresis. Neural networks are introduced to handle the unknown dynamics, ensuring the convergence of consensus errors and further ensuring the transient performance of MASs. Simulation examples are included to verify the effectiveness of the control approach.
NONLINEAR DYNAMICS
(2021)
Article
Computer Science, Information Systems
Tianwei Zhou, Guanghui Yue, Ben Niu
Summary: In this paper, a novel quantization level based event-triggered control algorithm is proposed to guarantee the stability of the system. By exploring the characteristics of nonlinear networked control systems, two quantization level based event-triggered control mechanisms are developed. The simulation results demonstrate the feasibility and superiority of the proposed algorithms.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Ehsan Aslmostafa, Sehraneh Ghaemi, Mohammad Ali Badamchizadeh, Amir Rikhtehgar Ghiasi
Summary: This paper addresses the stability problem for a class of nonlinear systems in the form of strict-feedback with input quantization. It introduces a control scheme using a sector-bounded hysteresis quantizer to achieve signal quantization and reduce potential chattering. The control scheme stabilizes the uncertain nonlinear system using a common Lyapunov function and the backstepping method, without requiring global Lipschitz assumption and eliminating restrictions on quantization design parameters.
Article
Automation & Control Systems
Tianwei Zhou, Zhiqiang Zuo, Yijing Wang, Zhicheng Zhang, Shaoping Chang
Summary: In this article, a novel reference input and hysteresis quantizer based triggered control method is formulated to address the stability issues in networked control systems over limited channels. By designing local controllers and coders/decoders, Zeno behavior is successfully eliminated.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Mechanical
Mohammad Javad Mirzaei, Ehsan Aslmostafa, Mostafa Asadollahi, Mohammad Ali Badamchizadeh
Summary: In this article, a terminal sliding mode control strategy is proposed to address the synchronization problem for perturbed nonlinear systems. The use of a hysteresis quantizer effectively prevents the occurrence of adverse chattering phenomenon.
NONLINEAR DYNAMICS
(2022)
Article
Computer Science, Artificial Intelligence
Linlin Nie, Miaolei Zhou, Wenjing Cao, Xiaoliang Huang
Summary: This study proposes an adaptive fuzzy dynamic surface output feedback control method for a class of uncertain nonlinear systems subject to unknown input hysteresis. By using a Prandtl-Ishlinskii model to describe the unknown input hysteresis, the controller design becomes feasible. A nonlinear extended state observer is designed to estimate unmeasurable states and disturbances, while a novel nonlinear function replaces the fal() function for increased convergence speed. The proposed method is demonstrated to provide satisfactory tracking performance through experiments.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Yue Wang, Xiuyu Zhang, Zhi Li, Xinkai Chen, Chun-Yi Su
Summary: This article proposes a butterfly-like hysteresis model and a neural network based adaptive implicit inverse control scheme for describing and controlling butterfly-like hysteresis. The effectiveness of the proposed modeling and control methods is validated experimentally.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Lin Zhao, Jinpeng Yu, Xinkai Chen
Summary: This paper presents a neural network-based adaptive finite-time output feedback attitude tracking control method, which can effectively address issues such as actuator saturation, inertial uncertainty, and external disturbance in spacecraft. By designing a neural state observer and applying adaptive neural finite-time command filtered backstepping control, finite-time attitude tracking and controller state updating can be achieved. Numerical simulations confirm the effectiveness of the proposed algorithm.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Aerospace
Guozeng Cui, Hui Xu, Xinkai Chen, Jinpeng Yu
Summary: This article proposes a fixed-time distributed adaptive formation control algorithm under the event-triggered framework to guarantee the expected formation pattern for multiple quadrotor unmanned aerial vehicles (QUAVs) with full-state constraints. The algorithm effectively handles the explosion of complexity and singularity problem. It also improves control performance through error compensation mechanism. The stability analysis proves that the developed control scheme ensures bounded signals and convergence of formation tracking errors in a fixed time. Simulation examples validate the effectiveness of the proposed algorithm.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2023)
Article
Automation & Control Systems
Xiuyu Zhang, Yuehang Liu, Xinkai Chen, Zhi Li, Chun-Yi Su
Summary: This article proposes an adaptive pseudoinverse control scheme based on fuzzy logic system (FLS) and barrier Lyapunov function (BLF) for a class of state-constrained hysteretic nonlinear systems. The hysteresis nonlinearity in the actuators is considered and mitigated by the proposed pseudoinverse control algorithms. The all-state-constrained control problem of the Preisach hysteresis model is overcome with the aid of an FLS, BLFs, and the proposed hysteresis pseudoinverse algorithms.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Xiuyu Zhang, Hongzhi Xu, Xinkai Chen, Zhi Li, Chun-Yi Su
Summary: This article proposes a novel robust adaptive piecewise indirect inverse output-feedback control scheme to mitigate butterfly-like hysteresis with creep in smart material actuators. Piecewise indirect inverse indicates that it is not a true hysteresis and creep inverse compensator, but an online decoupling mechanism to accessing the approximately actual control signal from the designed hysteretic and creeping temporary control signal. In addition, a new butterfly-like relay operator is proposed for the first time, leading to the construction of a new model of butterfly-like hysteresis with creep. Finally, the experimental results on the dielectric elastomer actuator motion control platform illustrate the effectiveness of the proposed output-feedback control scheme.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhen Liu, Xinkai Chen, Jinpeng Yu
Summary: This article investigates the security control issue for stochastic Markov jump cyber-physical systems against actuator failures, randomly occurring injection attacks, and inaccessible states using state estimator-based adaptive sliding mode control strategy. An estimator is used to generate the knowledge of states and establish a new switching surface. An adaptive sliding mode control is developed to ensure the attainability of the switching surface under stochastic noise, unknown injection attacks, and potential actuator failures. A new stochastically stable criterion for the target system is deduced based on the switching surface and stochastic stability theory. A simulation study is conducted to verify the proposed control scheme using a tunnel diode circuit model.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Xiuyu Zhang, Yue Wang, Guoqiang Zhu, Xinkai Chen, Chun-Yi Su
Summary: This article proposes a discrete-time adaptive dynamic surface control scheme for the control of a quadrotor unmanned aerial vehicle, overcoming the challenges of strong nonlinearities, coupling, and underactuation. The designed robust adaptive control method and adaptive neural control equations are used to address the nonlinearities, couplings, and underactuation. Compared to continuous-time control, discrete-time control is more suitable for practical computer and network control applications. The use of digital first-order low-pass filters in the backstepping method eliminates the model transformation problem.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Gang Li, Jinpeng Yu, Xinkai Chen
Summary: In this article, an adaptive fuzzy neural network (NN) command filtered impedance control method is proposed for constrained robotic manipulators with disturbance observers. The barrier Lyapunov functions are introduced to handle the full-state constraints, and the adaptive fuzzy NN is utilized to handle the unknown system dynamics. A disturbance observer is designed to eliminate the effect of unknown bound disturbance. The effectiveness of the proposed control method is validated through simulation studies.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Zhengqiang Zhang, Chen Yang, Xinkai Chen
Summary: This article studies the decentralized robust model reference adaptive control (MRAC) problem for a class of large-scale systems with unknown plant parameters, unknown time-varying delayed interconnections, and unknown dead-zone inputs. Two robust adaptive control schemes are proposed for symmetric and asymmetric dead-zone input cases, respectively, assuming moderate time-delay nonlinearity and matching conditions of the plant model and the reference model matrix. The control gain function is explicitly expressed, and its useful properties are established. A Lyapunov-Krasovskii functional with two integral functions is constructed. It is shown that all signals in the closed-loop system are bounded, and the state tracking error converges exponentially to a tunable region. The effectiveness and feasibility of the proposed design approach are illustrated by a simulation example.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Yue Wang, Xiuyu Zhang, Shunjiang Wang, Zhi Li, Xinkai Chen, Chun-Yi Su
Summary: This article proposes a decentralized adaptive implicit inverse control scheme based on fuzzy-logic systems (FLSs) for a class of large-scale nonlinear systems with time delays and multihysteretic loops. The novel algorithms feature hysteretic implicit inverse compensators to mitigate multihysteretic loops effectively. The authors provide three contributions: 1) a searching mechanism to obtain the approximate value of the practical input signal from the hysteretic temporary control law; 2) the attainment of arbitrarily small L∞ norm of the tracking error by utilizing the proposed initializing technique, which combines FLSs and a finite covering lemma to deal with time delays; and 3) the construction of a triple-axis giant magnetostrictive motion control platform to validate the effectiveness of the proposed control scheme and algorithms.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Yanzheng Zhu, Jian Zhang, Liheng Chen, Xinkai Chen, Chun-Yi Su
Summary: This paper investigates the fault estimation problem for unmanned marine vehicles with sensor faults and non-differentiable actuator faults. Two learning observer methods are proposed to resolve the non-differentiable actuator faults. Simulation results show the effectiveness of the proposed methods.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Robotics
Jichun Xiao, Lina Hao, Hongzhi Xu, Xu Zhang, Xing Li, Zhi Li
Summary: Payload capacity is crucial for climbing robots, and many legged robots prioritize foot design over payload capacity. This study proposes a novel adhesion foot structure utilizing micro-suction tape and a detachment mechanism to improve payload capacity of climbing robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
