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Article
Computer Science, Artificial Intelligence
Fanrong Qu et al.
Summary: This article investigates the chance-constrained $H_{infinity}$ state estimation problem for a class of time-varying neural networks subject to measurements degradation and randomly occurring deception attacks. A novel energy-constrained deception attack model is proposed, and the explicit expression of the estimator gains is derived by solving a minimization problem. Numerical examples and a practical three-tank system are used to demonstrate the correctness and effectiveness of the proposed estimation scheme.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Zhihua Wu et al.
Summary: This article investigates the security issues when electric vehicles (EVs) are incorporated into the load frequency control (LFC) system. It proposes a networked LFC system and an H-infinity sliding mode observer (SMO) to accurately estimate the internal physical state of the system. Additionally, a dual time-varying coding detection scheme and algorithm are established to detect and disclose covert attacks.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Automation & Control Systems
Yan Li et al.
Summary: This article discusses decentralized event-triggered synchronization control for complex networks under nonperiodic DoS attacks. An event-based synchronization error model is established and sufficient conditions for secure synchronization are analyzed using Lyapunov stability theory. The synchronization controller gains are designed using linear matrix inequalities.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Shuangxin Zhu et al.
Summary: This article addresses the adaptive torus-event-based Script capital H-infinity control problem for a class of networked Takagi-Sugeno (T-S) fuzzy systems under deception attacks, utilizing a unified framework and Lyapunov function to derive the necessary conditions for controller design. The study uses an adaptive communication mechanism and fuzzy controllers to ensure system stability and disturbance suppression in the presence of deception attacks, with controller gains calculated via linear matrix inequalities.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Engineering, Electrical & Electronic
Weilin Yang et al.
Summary: This study proposes a self-triggered pseudo terminal ingredient approach for classic dual-mode robust model predictive control of discrete-time linear systems. By using offline design of pseudo terminal set and pseudo terminal cost, the online optimization problem is transformed into several subproblems with short prediction horizons. The proposed approach can guide the system state into a predetermined terminal constraint set via intermittent sampling, reducing computational and communication burden for the online part.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2022)
Article
Engineering, Electrical & Electronic
Rong Nie et al.
Summary: The study utilizes dynamic event-triggered sliding mode control to address consensus tracking, introducing a mechanism to avoid redundant data transmission and designing a sliding mode surface to ensure consensus tracking through sufficient conditions.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2022)
Article
Computer Science, Artificial Intelligence
Zhenhui Xu et al.
Summary: A novel IRL algorithm is proposed in this article to solve the optimal control problem for continuous-time nonlinear systems with unknown dynamics. By embedding an auxiliary trajectory to learn the optimal solution, the algorithm guarantees convergence and stability of the closed-loop system.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Shaohua Luo et al.
Summary: This article proposes a hierarchical neural network structure to solve the problem of optimal synchronization for coupled fractional-order chaotic electromechanical devices. The presented scheme includes an adaptive neural feedforward policy and an optimal neural feedback policy to force the slave system to synchronize with the master system. The simulation results verify the effectiveness of the proposed scheme in achieving optimal synchronization and maintaining dynamic stability.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Hong Wang et al.
Summary: This article presents an off-policy model-free algorithm based on reinforcement learning to optimize cooperative consensus problem of nonlinear continuous-time multiagent systems. It transforms the problem and proposes a policy iteration algorithm to solve it effectively. Then, a model-free Bellman equation is derived to find the optimal value function and control policy. Finally, an off-policy model-free integral RL algorithm is proposed to optimize the FC consensus problem of the whole system in real time using measured data.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Automation & Control Systems
Lijuan Zha et al.
Summary: This article addresses the problem of $H_{infinity}$ output feedback control for event-triggered networked systems subject to multiple cyber attacks, considering dynamic event-triggered schemes and the effects of the attacks. A sufficient condition is derived to guarantee asymptotic mean-square stability and a prescribed $H_{infinity}$ performance of the closed-loop system. The effectiveness of the proposed method is illustrated through an example.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Artificial Intelligence
Ziquan Yu et al.
Summary: This article proposes a fractional-order intelligent fault-tolerant synchronization tracking control scheme for multiple unmanned airships (UAs). The scheme incorporates recurrent fuzzy neural networks, fractional calculus, and fixed-time prescribed performance functions (PPFs) into a unified framework to achieve high-precision control. Experimental results demonstrate the effectiveness of the proposed scheme.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Information Systems
Jinliang Liu et al.
Summary: This paper investigates the design of a security tracking controller for discrete-time networked control systems with stochastic cyber-attacks using a dynamic event-triggered communication approach. The approach adjusts the amount of data transmission in the network based on the variation of the tracking error while maintaining the tracking performance of the system. The paper provides a sufficient condition for asymptotic stability of the tracking error system using Lyapunov stability theory and co-designs the tracking controller gain and event-triggering parameter by solving a linear matrix inequality. Simulation examples are presented to validate the theoretical results.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Xiong Yang et al.
Summary: This article introduces an optimal event-driven control scheme for a continuous stirred tank reactor (CSTR) system, utilizing discounted cost and adaptive critic designs to solve the optimal event-driven control problem. Stability analysis of signals in the closed-loop system is conducted using the Lyapunov approach.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Bo Pang et al.
Summary: This article studies the infinite-horizon adaptive optimal control of continuous-time linear periodic systems and proposes a novel value iteration-based off-policy adaptive dynamic programming algorithm for a general class of systems. The algorithm is proven to uniformly converge to optimal solutions in both model-based and model-free cases, without assuming knowledge of an initial stabilizing controller. Application to a triple inverted pendulum demonstrates the feasibility and effectiveness of the proposed method.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Xiong Yang et al.
Summary: This article introduces a novel decentralized event-triggered control scheme for continuous-time nonlinear systems with matched interconnections, utilizing reinforcement learning to solve optimal control problems and achieve system stability.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Automation & Control Systems
Jinliang Liu et al.
Summary: This paper investigates the controller design problem of networked control systems subject to cyber attacks, using a hybrid-triggering communication strategy to save limited communication resources. The stability criterion for system stabilization is obtained by employing Lyapunov stability theory and stochastic analysis techniques. Furthermore, the desired controller gain is derived through matrix inequalities, and a numerical example is used to demonstrate the utility of the proposed scheme.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Ning Wang et al.
Summary: The article introduces a novel self-learning-based model-free solution, DPRLC, for optimal control and prescribed tracking accuracy of USVs in complex marine environments. The scheme utilizes data-driven performance-prescribed reinforcement learning to convert constrained tracking errors into constraint-free stabilization for controller synthesis optimization. Theoretical analysis proves the effectiveness and superiority of the DPRLC scheme in guaranteeing prescribed tracking accuracy while minimizing costs.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Automation & Control Systems
Xiong Yang et al.
Summary: This article addresses an event-driven H-infinity control problem for continuous-time nonlinear systems with asymmetric input constraints. By converting the problem into a two-person zero-sum game and developing a novel event-triggering condition to exclude Zeno behavior, the study provides a solution for handling the issue effectively. Utilizing adaptive critic learning framework, a single critic network is used to solve the event-driven Hamilton-Jacobi-Isaacs equation and demonstrate the guaranteed uniform ultimate boundedness of all signals in the closed-loop system.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Automation & Control Systems
Jinliang Liu et al.
Summary: This article focuses on security control for Takagi-Sugeno fuzzy systems with adaptive event-triggered mechanism and multiple cyber-attacks. A mathematical model is proposed for T-S fuzzy systems with multiple cyber-attacks and AETM, ensuring system stability using Lyapunov stability theory and deriving controller gains with a linear matrix inequality technique. Simulated examples demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Yueying Wang et al.
Summary: This article presents a fault-tolerant tracking control strategy for Takagi-Sugeno fuzzy model-based nonlinear systems which combines integral sliding mode control with adaptive control technique. The strategy ensures the accessibility of the sliding motion despite the effect of actuator faults and unknown disturbances by designing an appropriate fuzzy integral switching surface. It is verified by applying it to the dynamic positioning control of unmanned marine vehicles.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Tong Wang et al.
Summary: This article investigates event-triggered adaptive tracking control for a class of pure-feedback stochastic nonlinear systems with full state constraints and input saturation. The proposed method transforms the pure-feedback structure into a strict-feedback case and introduces a novel event-triggered adaptive fuzzy tracking control scheme with a relative threshold. The effectiveness of the approach is verified through simulation studies, demonstrating the stability and state constraint preservation of the system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Zhengqiang Zhang et al.
Summary: This article considers tracking control for uncertain multi-input-multi-output nonlinear systems, proposing three stable adaptive tracking schemes using different control algorithms. The schemes achieve bounded-error tracking, asymptotic tracking, and exponential tracking for a given reference signal. The effectiveness of the proposed control algorithms is demonstrated on a nonlinear chaotic Chua's circuit with comparative simulation studies.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Shan Xue et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Automation & Control Systems
Xiong Yang et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Automation & Control Systems
Bo Zhao et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2020)
Article
Automation & Control Systems
Shu Li et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Automation & Control Systems
Deyin Yao et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Automation & Control Systems
Huaguang Zhang et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Automation & Control Systems
Yuanheng Zhu et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2020)
Article
Computer Science, Artificial Intelligence
Jinna Li et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2019)
Article
Automation & Control Systems
Zhaoxu Yu et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2018)
Article
Computer Science, Artificial Intelligence
Ning Wang et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2018)
Article
Automation & Control Systems
Chao Li et al.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2018)