Article
Computer Science, Artificial Intelligence
Libin Wang, Huanqing Wang, Peter Xiaoping Liu, Song Ling, Siwen Liu
Summary: This article presents a fuzzy finite-time command filtering output feedback control method for a class of nonlinear systems. The method solves the computational complexity problem and ensures the finite-time boundedness of signals and convergence of tracking error by introducing fuzzy logic system and fuzzy state observer.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Jian Chen, Hak-Keung Lam, Jinpeng Yu
Summary: This article studies the adaptive fuzzy event-triggered output feedback control for nonlinear systems with nonstrict feedback structure and variable disturbances. By proposing a fuzzy state observer with an adaptive parameter and constructing various control components, the adaptive fuzzy output feedback control scheme is built to ensure bounded signals and finite-time tracking errors. Simulation examples confirm the effectiveness of the proposed method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Huan Yu, Miroslav Krstic
Summary: This paper proposes an output feedback boundary control for mitigating traffic congestion on a two-lane freeway segment. By stabilizing traffic flow through velocity and density control, improvements in fuel consumption, driver comfort, and total travel time are shown.
Article
Automation & Control Systems
Lian Chen, Qing Wang, ChangHua Hu
Summary: This paper presents a new adaptive fuzzy command filtered backstepping controller for tracking control of non-affine pure-feedback systems with uncertain disturbances. The non-affine difficulty of pure-feedback systems is solved by employing the mean-value theorem, and fuzzy logic systems are used to estimate system uncertainties. The proposed control scheme ensures boundedness of all closed-loop signals and the ability of the system output to track the given reference signal. The developed approach extends the practical applications of classical command filtered schemes to uncertain non-affine pure-feedback systems and improves tracking performance compared to existing dynamic surface control proposals.
Article
Engineering, Mechanical
Shijia Kang, Peter Xiaoping Liu, Huanqing Wang
Summary: This paper presents a control scheme based on adaptive fuzzy approach for dealing with the finite-time prescribed performance control problem of large-scale nonlinear interconnected systems with input dead zone. By introducing specific functions and design, it solves the issues in conventional backstepping control and ensures that signals in the control system are bounded, with output errors reaching a predefined range within a finite time.
NONLINEAR DYNAMICS
(2021)
Article
Automation & Control Systems
Xiujuan Zhao, Shiming Chen, Zheng Zhang, Yuanshi Zheng
Summary: This article addresses the issue of adaptive scaled consensus tracking control for uncertain nonlinear multiagent systems. A new form of nonlinear MAS is proposed, and a state observer based on adaptive radial basis function neural networks is developed. A command filter control scheme is used to handle the complexity derived from the conventional backstepping design, and a compensation control strategy is employed to deal with input delays and uncertain control direction. An adaptive output feedback control approach is proposed for constructing the scaled consensus tracking control protocol. The effectiveness of the approach is verified through numerical simulations.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Yanchun Bai, Jian Hu, Jianyong Yao
Summary: This paper focuses on the high-performance tracking control of electromechanical servo systems. A novel neural network state observer is designed to observe the unknown states. The proposed observer has higher observation accuracy and better robustness compared to existing neural network observers. Additionally, a fixed-weight single-node neural network is added to effectively improve the approximation ability of the double-layer neural network.
Article
Computer Science, Information Systems
Qingkun Yu, Xiqin He, Libing Wu, Liangdong Guo
Summary: This paper addresses the design of neural network observer and adaptive finite-time tracking controller for uncertain nonlinear systems with event-triggered inputs and unknown dead-zone constraints. By improving the finite-time command filter backstepping technique and developing an adaptive output feedback event triggering mechanism, the goal of finite-time convergence is achieved and network bandwidth is effectively saved.
INFORMATION SCIENCES
(2022)
Article
Engineering, Marine
Yuxian Huang, Yifei Hu, Jinbo Wu, Chenghao Zeng
Summary: This paper proposes a control strategy suitable for engineering applications to maintain a safe distance between the guide ship and approach ship during underway replenishment process. By using a leader-follower approach and designing an extended state observer, the expected distances between the two ships are ensured. The effectiveness of the proposed method is demonstrated through simulation verification.
Article
Automation & Control Systems
Zhenbin Du, Yonggui Kao, Ju H. Park
Summary: This paper addresses the interval type-2 fuzzy tracking control problem for nonlinear networked control systems with unreliable communication links. A tracking controller is designed for interval type-2 fuzzy sampled-data system under unreliable communication, enhancing stability through membership function characteristics and utilizing Lyapunov theory. The paper provides less conservative sufficient condition for designing networked tracking controller to ensure anticipated tracking performance, demonstrated through simulation examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Jianwei Xia, Jing Zhang, June Feng, Zhen Wang, Guangming Zhuang
Summary: In this paper, a command filter-based adaptive tracking controller is proposed to deal with a class of nonlinear systems with unknown control directions. The design process involves the use of a fuzzy logic system and Nussbaum function to handle nonlinear functions and compensate for the influence of unknown directions. The effectiveness of the control approach is demonstrated through a simulation example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Wangyao Xu, Ze Li, Guozeng Cui, Chengxi Wang, Fuyuan Hu
Summary: An adaptive fuzzy finite time command filter control scheme is proposed for a single machine infinite power system with static VAR compensator (SVC). The controller design takes unknown external interference into account and formulates the incomplete single machine infinite SVC power system in terms of fuzzy logic system. The devised control scheme ensures the convergence of rotor power angle and stability of all variables in the control system. Simulation results demonstrate the effectiveness of the proposed control scheme.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Mathematics, Applied
Bo Xu, Yanjun Liang, Yuan-Xin Li, Zhongsheng Hou
Summary: This paper considers the fixed-time adaptive tracking control issues of nonlinear systems with input quantization. By designing a common adaptive parameter, the overparameterization problem of existing results is resolved. The fixed-time adaptive tracking control is achieved based on command filter and backstepping technique. The Nussbaum-type function is adopted to handle quantized input, and fuzzy logic systems are used to approximate unknown nonlinearities. It is concluded that the proposed method can guarantee stability of the controlled system and boundedness of the signals. Simulation examples are provided to verify the effectiveness of the presented scheme.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Engineering, Mechanical
Yue Sun, Chuang Gao, Li-bing Wu, Yong-hui Yang
Summary: This paper proposes a fuzzy controller based on command filtered and event-triggered technology to improve the tracking error of nth-order uncertain nonlinear systems with sensor faults. A fault-tolerant control scheme is introduced to solve the problem of sudden output sensor failure. The proposed controller also avoids the complexity explosion problem of virtual control law derivations, making the design simpler. An effective observer is designed to solve the problem of system state immeasurability. According to Lyapunov stability theory, it is proved that all closed-loop signals are uniformly and ultimately bounded. Simulation examples demonstrate the effectiveness of the proposed scheme in second-order nonlinear systems and single-link robots.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Shuchao Hou, Lin Zhao
Summary: This article studies fixed-time output feedback tracking control for nonlinear systems based on the command filtered backstepping method. The neural network approximation technique is used to estimate uncertain dynamics. The fixed-time filter is introduced to overcome complexity explosion and is combined with a compensation signal to reduce filtering error. The results show that the proposed fixed-time control strategy successfully achieves the expected tracking error near the origin within a predetermined convergence time, without requiring knowledge of the system's initial value.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Ammara Mehmood, Peng Shi, Muhammad Asif Zahoor Raja, Aneela Zameer, Naveed Ishtiaq Chaudhary
Summary: This study introduces a novel implementation of evolutionary heuristics using backtracking search optimization algorithm (BSA) for accurate, efficient, and robust parameter estimation of power signal models. The fitness function is mathematically formulated by utilizing approximation theory in mean squared errors between actual and estimated responses, as well as, true and approximated decision variables. Variants of BSA-based meta-heuristics are applied for parameter estimation problem of power signals in different scenarios of noise variation.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Automation & Control Systems
Kamal Mammadov, Cheng-Chew Lim, Peng Shi
Summary: In this manuscript, we formulate the general Target-Attacker-Defender differential game in both continuous-time and discrete-time turn-based variants in n-dimensional Euclidean space. The objective of the Attackers is to get as close as possible to the Target before collision with the Defender, while the Target and Defender coordinate to achieve the opposite. We consider the most general setting for this zero-sum differential game, where the agents can move at different speeds, and prove the Nash equilibrium strategies in the discrete-time turn-based variant.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Ting Shi, Peng Shi, Liping Zhang
Summary: This paper investigates the leader-following consensus problem for general linear multi-agent systems under external disturbances. The communication topologies are time-varying and switched from a finite set. A switched control system is introduced to model these topologies, and the weighted L-2 - L-infinity performance is analyzed. A topology-dependent controller is designed based on local information from the neighbors. Conditions are developed for the existence of a control protocol that achieves the leader-following consensus with a certain level of weighted L-2 - L-infinity performance. The design algorithm is formulated as a set of linear matrix inequalities (LMIs), and a numerical example is provided to demonstrate the effectiveness of the proposed consensus algorithm.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Xin Yuan, Michael John Liebelt, Peng Shi, Braden J. Phillips
Summary: This paper focuses on developing agents with artificial general intelligence using a rule-based approach. The study demonstrates that association rules mining can be used to discover rules and determine relationships between data sets. The authors introduce a modified ARM method to discover rules for an agent-guided vehicle designed for autonomous parking, and validate the effectiveness of their approach through simulation testing.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Automation & Control Systems
Renjie Ma, Peng Shi
Summary: This paper presents defense strategies based on switched counteraction principle to protect the secure state estimation (SSE) of Cyber-Physical Systems (CPSs) from sparse data injection (DI) attacks. The physical layer is modeled using a hybrid mechanism and malicious injections are excluded through adaptively switched counteraction searching. The proposed design methods are demonstrated to be effective and promising through numerical examples.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Huiyan Zhang, Xiuli He, Luis I. Minchala, Peng Shi
Summary: This paper proposes a dissipativity-based dynamic output feedback controller design method for SemiMarkovian jump systems under stochastic cyber-attacks. By fractionalizing the time-varying transition probability matrix, the design method is improved and demonstrated to be effective through simulation results.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Computer Science, Information Systems
Li-sang Liu, Jia-feng Lin, Jin-xin Yao, Dong-wei He, Ji-shi Zheng, Jing Huang, Peng Shi
Summary: This paper established a map of an unknown indoor environment based on depth information via SLAM technology, and used Dijkstra algorithm as the global path planning algorithm and dynamic window approach (DWA) as the local path planning algorithm for obstacle avoidance in an autonomous driving car. The tests on the smart car proved the system can complete functions of environment map establishment, path planning, navigation and obstacle avoidance.
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Shiqi Zheng, Peng Shi, Shuoyu Wang, Yan Shi
Summary: This article studies the adaptive neural controller design for uncertain multiagent systems, utilizing neural networks to approximate unknown nonlinearities, constructing new Lyapunov functions to guarantee the conditions of NNs, and proposing new adaptive neural PI-type controllers. Illustrative examples demonstrate the advantages of the obtained results.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Automation & Control Systems
Mei Fang, Peng Shi, Shanling Dong
Summary: This paper considers the problem of sliding mode control for a class of nonlinear continuous-time Markov jump systems with uncertainties and time delay. A novel integral-type switching sliding surface function is designed, and an SMC law is constructed to force system trajectories onto the specified switching sliding surface. Stochastic stability and dissipative performance of sliding mode dynamics are analyzed, and a delay-dependent sufficient condition for the existence of the desired switching surface is developed. Additionally, the study extends SMC to investigate finite-time stability during both reaching and sliding motion phases in the stochastic setting, with simulation results illustrating the effectiveness of the proposed design techniques.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Chaoxu Guan, Zhongyang Fei, Hamid Reza Karimi, Peng Shi
Summary: This paper introduces a new method for finite-time H-infinity synchronization of discrete-time switched neural networks, and designs a quantized state feedback controller to ensure synchronization. The conservatism is reduced by the mode-dependent and semi-time-dependent controller.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Marine
Yuanjie Ren, Lanyong Zhang, Peng Shi, Ziqi Zhang
Summary: A hierarchical collaborative control energy management scheme is proposed for the propulsion system of hybrid electric ships. The scheme effectively solves the problems of steady-state oscillation and deviation from the tracking direction caused by volatility and uncertainty, achieving significant improvement.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Huiyan Zhang, Hao Sun, Peng Shi, Luis Ismael Minchala
Summary: This article proposes a novel chip detection method that combines attentional feature fusion and cosine nonlocal attention to effectively handle chip images with multiple classes or complex backgrounds. Experimental results demonstrate that the proposed method outperforms the benchmark method on a medium-scale dataset.
Article
Remote Sensing
Yang Fei, Yuan Sun, Peng Shi
Summary: In this study, a hierarchical formation control strategy is used to address the robust formation control problem for a group of UAVs with system uncertainty. A sliding mode neural-based observer is constructed to estimate the nonlinear uncertainty in the UAV model, and sliding mode controllers and differentiators are designed to alleviate chattering in the control input. The proposed control scheme's effectiveness is validated through Lyapunov stability theory and numerical simulations on a multiple-UAV system.
Article
Engineering, Electrical & Electronic
Guidong Zhang, Peiwei Zheng, Shenglong Yu, Hieu Trinh, Peng Shi
Summary: This article investigates the controllability of high-order DC-DC converters, analyzing their structure controllability, state controllability, and output controllability through established mathematical models. The theoretical analysis is supported by simulation and experimental verification on a four-cell switched-inductor DC-DC converter, providing a theoretical framework and references for parameter and control designs for high-order converters in practical applications.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2021)
Article
Computer Science, Artificial Intelligence
Shiqi Zheng, Peng Shi, Shuoyu Wang, Yan Shi
Summary: This article explores the decentralized stabilization problem of stochastic interconnected systems, proposing state and output feedback controllers for these systems with the use of barrier Lyapunov-Krasivskii functions for stability analysis. Fuzzy systems are adopted to approximate complex and unknown dynamics, proving that all states will stay within a compact set using barrier functions and switching mechanism. An adaptive compensator is presented to handle errors from input quantization, achieving asymptotic stability of the interconnected systems.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
