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Automation & Control Systems
Pengwei Shi et al.
Summary: This paper proposes an adaptive robust synchronous control scheme based on an improved master-slave structure, which is not only simple in structure but also easy to implement in engineering. The established error dynamics model compensates for the lag of response of traditional master-slave control and improves the stability of the closed-loop system. Online parameter adaptive algorithms deal with parameter uncertainties, while robust control deals with unmodeled dynamics and external disturbances. Additionally, nonlinear cogging force compensation is applied to improve control accuracy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Fanghua Tang et al.
Summary: In this paper, an adaptive fuzzy tracking control method is proposed for switched multi-input multi-output nonlinear systems with time-varying full state constraints and unknown control directions. The method utilizes fuzzy logic systems to approximate unknown dynamic functions and solves the problems of time-varying full state constraints and unknown control directions. The designed control scheme ensures bounded system signals and convergence of tracking error to zero.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Automation & Control Systems
Yanwei Zhao et al.
Summary: This paper explores the issue of adaptive neural decentralised tracking control for a class of output-constraint switched interconnected nonlinear systems with unknown backlash-like hysteresis control input. The proposed method uses neural networks to approximate unknown nonlinear functions and design a switched state observer, and solves the problem of output constraints by introducing barrier Lyapunov functions. The Lyapunov stability theory is used to verify the boundedness of all signals in the switched closed-loop system. The effectiveness of the adaptive decentralised control scheme is demonstrated through numerical simulation results.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Liang Zhang et al.
Summary: This study investigates the real-time reachable set control problem for neutral singular Markov jump systems with mixed delays and bounded disturbance under non-zero initial conditions. The sufficient conditions for reachable set control are obtained using the free-weighting matrix method and Lyapunov stability theory with the linear matrix inequality technique. The controller gains of the closed-loop system are derived using the matrix decoupling method. The proposed method is validated using a practical application example of a direct current motor drive system.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Automation & Control Systems
Zhongyu Chen et al.
Summary: This article proposes a command filtering-based adaptive event-triggered neural network control scheme for uncertain switched nonlinear systems with unknown control coefficient and input saturation. The scheme utilizes radial basis function neural networks as function approximators and introduces an event-triggering mechanism based on tracking error to avoid excessive consumption of communication resources. It employs command filters and error compensation signals to address the complexity explosion issue in conventional control design, and introduces a Nussbaum-type function to handle unknown control gain and input saturation. The stability of the closed-loop system is proven under a standard Lyapunov stability analysis framework. The effectiveness of the proposed control scheme is demonstrated through a simulation example.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Engineering, Mechanical
Shanlin Liu et al.
Summary: This paper focuses on the event-triggered control problem for unknown nonlinear systems with input constraints. By introducing a nominal system and a discounted cost function, the original problem is transformed into an event-triggered optimal control problem. A data-driven model using recurrent neural networks is designed to approximate the unknown dynamics of the system. A single critic neural network is constructed to solve the Hamilton-Jacobi-Bellman equation with multiple nonlinear terms. The update law of the critic NN is designed to relax the persistence of excitation condition. The proposed event-triggered optimal controller ensures the boundedness of state variables and critic NN weight errors based on Lyapunov stability theory. The effectiveness of the control scheme is demonstrated through simulation examples.
NONLINEAR DYNAMICS
(2022)
Article
Computer Science, Hardware & Architecture
Liang Zhang et al.
Summary: This paper investigates the asynchronous event-triggered state-feedback control for discrete-time nonlinear singular Markov jump systems subject to reachable set bounding and stochastic cyber-attacks. An event-triggered mechanism is introduced to regulate data transmission and save network resources. The secure asynchronous controller is designed to effectively resist the influence of attacks, and the reachable set analysis approach is used to ensure control error within the boundary.
IEEE-ACM TRANSACTIONS ON NETWORKING
(2022)
Article
Computer Science, Artificial Intelligence
Fabin Cheng et al.
Summary: This article presents an adaptive neural decentralized two-bit-triggered control method for interconnected large-scale nonlinear systems with actuator failures. The proposed control scheme, which combines radial basis function neural networks, a command filter, and backstepping recursive design, effectively addresses the problem of control signal transmission bit and ensures the system signals to be bounded and exhibit good tracking performance.
Article
Automation & Control Systems
Huijun Gao et al.
Summary: This article proposes a hierarchical multiobjective heuristic (HMOH) to optimize printed-circuit board assembly (PCBA) in a single beam-head surface mounter. By applying a novel decomposition strategy, the real-world PCBA optimization problem is closely modeled as the head task assignment problem (HTAP) and the pickup-and-place sequencing problem (PAPSP), resulting in successful real-time decision making.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Zhitai Liu et al.
Summary: This article proposes an approximation-free robust synchronization control scheme for dual-linear-motors-driven systems. It achieves high-precision tracking and synchronization performance without requiring explicit system model, reducing computational burden and complexity. The concept of prescribed performance is adopted to guarantee control effect and state constraints.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Jing Zhang et al.
Summary: This article investigates a decentralized adaptive neural network event-triggered sensor failure compensation control issue for nonlinear switched large-scale systems. A novel observer is designed for estimating unmeasured states, NNs are utilized for identifying uncertainties, a fault compensation mechanism is proposed, and a switching threshold strategy is developed to ensure bounded closed-loop signals. The proposed strategy is shown to effectively avoid Zeno behavior through simulation results.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Mathematics, Applied
Zhongyu Chen et al.
Summary: This paper presents a model-based adaptive event-triggered control scheme for uncertain single-input and single-output systems by constructing an adaptive model and using neural networks to approximate nonlinear functions. The stability of the resulting impulsive dynamic system is proven using Lyapunov theory, and the event-trigger condition reduces waste of communication resources by updating NN weights and feedback signals only when necessary.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Shuai Sui et al.
Summary: This article introduces a novel adaptive switching dynamic surface control strategy for fractional-order nonlinear systems, utilizing fractional-order Lyapunov stability criterion for designing control laws and adaptive laws. By combining universal approximation of neural networks and compensation technique of unknown dead-zones, an adaptive switching DSC controller is developed to ensure stability of switched fractional-order systems in the presence of unknown dead-zones and arbitrary switchings.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Automation & Control Systems
Li Ma et al.
Summary: This study addresses the issue of adaptive neural fault-tolerant control for uncertain switched nonstrict-feedback nonlinear systems by using radial basis function neural networks to identify uncertain parts. A controller with only three adaptive laws is developed based on small-gain technique, input-to-state practical stability theory, and common Lyapunov function approach. The designed controller ensures bounded closed-loop signals under arbitrary switching and convergence of tracking error to a small area around the origin.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Zhouhua Peng et al.
Summary: This article presents a modular design approach for event-triggered dynamic surface control of an underactuated autonomous surface vehicle to circumnavigate a dynamic target with unknown velocity. A stable closed-loop system is established by estimating the relative motion between the target and the vehicle and online modeling the unknown vehicle kinetics.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Automation & Control Systems
Yi Chang et al.
Summary: This paper investigates the issue of adaptive fuzzy tracking control for a class of pure-feedback switched nonlinear systems with unknown gain. By utilizing the mean value theorem and Nussbaum-type functions, an effective controller is designed to simplify the calculation. The stability of the system is ensured through the average dwell time method and Lyapunov theorem, with errors adjustable to be arbitrarily small.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Huanqing Wang et al.
Summary: This paper investigates fuzzy-based adaptive event-triggered tracking control for a class of non-strict-feedback nonlinear systems within fixed-time interval. Fuzzy logic system approximates unknown nonlinearities, event-triggered mechanism schedules data transmission dependent upon errors exceeding threshold. A fuzzy-based adaptive event-triggered controller is developed using backstepping design algorithm and Lyapunov stability theorem, ensuring singularity problem elimination, boundedness of closed-loop signals, and tracking error convergence.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2021)
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Siwen Hao et al.
Summary: This article proposes a decentralized adaptive fixed-time fault-tolerant control method for nonlinear systems, guaranteeing stability and performance of the system through backstepping technique.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2021)
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Bo Wang et al.
Summary: In this paper, a new neural network-based fault-tolerant active control is proposed for fractional time-delayed systems to address faults and uncertainties. By integrating a neural network estimator with active control, uncertainties and disturbances can be compensated for, improving the controller's performance in real applications. Simulation results demonstrate the effectiveness of the proposed control technique for uncertain time-delayed nonlinear systems.
Article
Automation & Control Systems
Jianwei Xia et al.
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)
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Jie Lian et al.
SYSTEMS & CONTROL LETTERS
(2020)
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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2020)
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(2018)
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(2017)
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(2017)
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(2017)
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INTERNATIONAL JOURNAL OF CONTROL
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