Article
Automation & Control Systems
Yongliang Yang, Majid Mazouchi, Hamidreza Modares
Summary: This article presents a new approach for mixed H-2/H-infinity performance optimization, formulating it as a nonzero-sum game and deriving the existence condition of the Nash equilibrium using Hamilton-Jacobi theory. Hamiltonian-driven inequalities are introduced to evaluate the performance, and a novel mixed policy iteration algorithm is developed for performance improvement and guarantee. The constrained-driven approach allows for considering both robustness and performance objectives in the PI algorithm.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Ning Li, Hongbin Wang, Qianda Luo, Wei Zheng
Summary: This paper investigates the robust H-infinity optimal formation control for the position subsystem of quadrotor unmanned aerial vehicles (UAVs) subject to external disturbances and collision constraints. To prevent collision with both members of the formation and external obstacles, a collision avoidance potential function is constructed using relative position and velocity information. The basic bounded control input can ensure the stable flight and collision avoidance of a quadrotor UAV system.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Information Systems
Jingwei Lu, Qinglai Wei, Ziyang Wang, Tianmin Zhou, Fei-Yue Wang
Summary: This paper introduces a novel event-triggered optimal control method for discrete-time multi-player non-zero-sum games. By combining event-triggered algorithm with parallel control, the system's asymptotic stability can be achieved and an upper bound for the sum of all players' actual performance indices can be determined in advance.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Chunbin Qin, Xiaopeng Qiao, Jinguang Wang, Dehua Zhang, Yandong Hou, Shaolin Hu
Summary: In this article, an adaptive robust stabilization scheme based on the control barrier function (CBF) is proposed for the nonzero-sum (NZS) differential games problem of uncertain nonlinear systems with state constraints, considering random disturbances and control input matrix uncertainty. The nominal system of the original system is adopted to deal with the impact of uncertainty, converting the robust regulation problem of multiplayer differential games into an optimal regulation problem. Each player only needs a critic neural network (NN) to approach the corresponding cost function, and the combination of the cost function and the CBF ensures the evolution of system states in the safe area. Under the influence of random disturbances and state constraints, the state and critic NN weights of the closed-loop system are guaranteed to be uniformly ultimately bounded (UUB) by combining with the Lyapunov stability theory. Two simulation examples are provided to verify the validity of the proposed scheme.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Pawel Penar, Zenon Hendzel
Summary: This paper presents an experimental verification of the application of differential games theory in real-time control of a nonholonomic, nonlinear dynamic system, using a wheeled robot as an example. The use of H-infinity (L-2 gain) control theory and a neural network solution of the Hamilton-Jacobi-Isaac equation in the actor-critic structure resulted in very good quality tracking control of the wheeled robot, considering changing working conditions and disturbances.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Pengda Liu, Huaguang Zhang, Jiayue Sun, Zilong Tan
Summary: This paper proposes a novel method to solve the problem of incomplete known dynamics in nonlinear systems zero-sum games. The method introduces discounted cost and integral reinforcement learning to obtain approximate optimal strategy pairs, and improves algorithm efficiency through the use of event-triggered mechanism.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Engineering, Mechanical
Yu Huo, Ding Wang, Junfei Qiao, Menghua Li
Summary: This paper proposes a novel optimal control scheme based on the adaptive critic technology to solve the multi-player zero-sum game issue of continuous-time nonlinear systems with control constraints and unknown dynamics. A neural network-based identifier is used to reconstruct the unknown system dynamics, and a new nonquadratic function is developed to derive the associated Hamilton-Jacobi-Isaacs equation of the constrained game. An adaptive critic framework is then constructed to approximate the optimal cost function and estimate the optimal control strategy sets and worst disturbance. Theoretical analysis using Lyapunov stability theorem proves the uniform ultimate boundedness stability of the system state and the critic network weight approximation error. A representative example is simulated to validate the efficacy of the proposed framework.
NONLINEAR DYNAMICS
(2023)
Article
Computer Science, Artificial Intelligence
Hongbing Xia, Bo Zhao, Ping Guo
Summary: In this paper, a synergetic learning structure-based neuro-optimal fault tolerant control method is proposed for unknown nonlinear continuous-time systems with actuator failures. The optimal control input and the actuator failure are treated as two subsystems under the framework of synergetic learning structure. The fault tolerant control problem is then formulated as a two-player zero-sum differential game. A radial basis function neural network-based identifier is constructed to identify the completely unknown system dynamics. The Hamilton-Jacobi-Isaacs equation is solved using an asymptotically stable critic neural network, and the stability of the closed-loop system is guaranteed by Lyapunov stability analysis.
Article
Automation & Control Systems
Xin Li, Ding Wang, Jiangyu Wang, Junfei Qiao
Summary: A multi-step adaptive critic control (MsACC) framework is developed to attenuate the effect of disturbances on control performance for discrete-time nonlinear systems. The MsACC algorithm achieves faster solution of the Hamilton-Jacobi-Isaac equation through multi-step policy evaluation compared to one-step policy evaluation. The convergence rate of the MsACC algorithm can be adjusted by varying the step size of policy evaluation. The effectiveness of the MsACC algorithm is verified through simulation examples of a linear system and a nonlinear plant.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Hao Ren, Bin Jiang, Yajie Ma
Summary: This article proposes a zero-sum differential game-based control scheme for a certain type of affine nonlinear control systems with actuator faults. By introducing Nash equilibrium and adaptive dynamic programming, the system stability and optimal performance are achieved.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Yajie Ma, Qingyuan Meng, Bin Jiang, Hao Ren
Summary: In this paper, a fault-tolerant control scheme is developed for second-order nonlinear control systems under actuator bias faults and loss of effectiveness faults using the zero-sum differential game method. A controller is designed based on the backstepping method to ensure system tracking performance, and a fault-tolerant controller is designed for the equivalent error system using the zero-sum differential game method. Simulation results demonstrate the effectiveness of the designed fault-tolerant control scheme.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mathematics, Applied
Marco Cococcioni, Lorenzo Fiaschi, Luca Lambertini
Summary: This paper focuses on solving zero-sum games involving infinite and infinitesimal payoffs by extending the Gross-Simplex algorithm to handle non-Archimedean quantities. The authors conducted four numerical experiments to test the correctness and efficiency of the Gross-Matrix-Simplex algorithm, emphasizing the difference between numerical and symbolic calculations.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Jing-Wen Xing, Chen Peng, Zhiru Cao
Summary: This paper proposes an event-triggered adaptive fuzzy tracking control method for high-order stochastic nonlinear systems. The fuzzy logic systems (FLSs) approximation approach is extended to handle the unknown nonlinear uncertainties. A novel high-order adaptive fuzzy tracking controller is presented using a backstepping approach and event-triggering mechanism, which reduces unnecessary waste of computation and communication resources. The effectiveness of the proposed control method is demonstrated through a numerical example.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Yongwei Zhang, Bo Zhao, Derong Liu, Shunchao Zhang
Summary: This article proposes a novel event-triggered control approach based on deterministic policy gradient adaptive dynamic programming algorithm to address zero-sum game problems for discrete-time nonlinear systems. By updating the controller aperiodically, adopting the actor-critic-disturbance framework, and providing a neural network weight updating law, the method effectively ensures the input-to-state stability and the uniform ultimate boundedness of weight estimation errors. The validity of the approach is verified through simulation of two DT nonlinear systems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Shan Xue, Biao Luo, Derong Liu, Yin Yang
Summary: In this article, an event-triggered H-infinity control method based on adaptive dynamic programming (ADP) with concurrent learning is proposed for unknown continuous-time nonlinear systems with control constraints. System identification based on neural networks (NNs) is used to identify completely unknown systems. A critic NN is employed to approximate the value function. A novel weight updating rule is developed based on the event-triggered control law and time-triggered disturbance law to reduce controller execution times and guarantee system stability. Concurrent learning is applied to the weight updating rule to relax the demand for traditional persistence of excitation condition. Simulation results demonstrate the effectiveness of the developed constrained event-triggered ADP method.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Yi Yu, Guo-Ping Liu, Xingwei Zhou, Wenshan Hu
Summary: This article presents a novel blockchain technology-assisted networked predictive secure control approach to enhance the security and stability of networked control systems (NCSs). By introducing blockchain technology and designing networked predictive control, the issues of real-time performance and security in NCSs are addressed.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Zhong-Hua Pang, Cheng-Gang Xia, Ji Zhang, Qing-Long Han, Guo-Ping Liu
Summary: This brief introduces a networked model predictive control (MPC) strategy for the finite-time convergence of networked control systems with two-channel random communication constraints. It transforms network-induced delays and packet dropouts into equivalent delays in each channel, which are actively compensated in the controller and actuator. By using a finite-time MPC strategy, future control inputs are obtained, and the upper bound of the convergence time is analytically determined. The proposed scheme is verified through a numerical simulation of a mass-spring-damper system.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Yi Yu, Guo-Ping Liu, Xiaoran Dai, Wenshan Hu
Summary: A novel coordinated control method based on multistep state predictions with active compensation of delay is proposed to address the poor dynamic consensus performance of currents in modular dc-dc converters. The method includes the design of a multistep state predictor and the optimization of the coordinating cost of currents. By minimizing a distributed coordinating performance index function, the optimal control protocol is derived to minimize the consensus error between output currents and compensate for communication constraints. The performance of the proposed scheme is verified through case studies in an experimental testbed.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Chuan-Dong Bai, Tong Mu, Zhong-Hua Pang, Jian Sun, Guo-Ping Liu
Summary: In this paper, a novel networked predictive control (NPC) method is proposed to compensate for the random communication constraints in a networked control system. The method handles the two-channel communication constraints separately based on their different features and uses actual control inputs instead of predicted ones. The proposed method achieves the same output tracking performance as the corresponding local control system and is validated by simulation and experimental results.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Automation & Control Systems
Xiaoran Dai, Guo-Ping Liu, Qijun Deng, Wenshan Hu, Pan Sun
Summary: A distributed cooperative control scheme is proposed for modular converters in ultra-large ship degaussing systems to improve magnetic stealth capability. Consensus and stability of the system are analyzed, and tailored controller design guidelines are presented. Simulation and experimentation confirm the efficacy of the control method.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Lei Cao, Da-Wei Zhang, Clara Mihaela Ionescu, Guo-Ping Liu
Summary: This paper investigates the formation consensus problem for a leader-follower networked multi-agent systems with communication constraints and switching topologies. A networked predictive control scheme is proposed to achieve stability and output formation consensus, compensating for data loss and time delays in the network. The sufficient and necessary condition of output formation consensus and stability for agents is given by equating the whole closed-loop networked multi-agent system with the proposed control scheme to the corresponding switched system. The proposed scheme is demonstrated to actively compensate for the communication constraints through numerical simulations and has a good control performance in practical experiments, realizing the formation task of the simulators.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Thermodynamics
Xiaoran Dai, Guo-Ping Liu, Wenshan Hu
Summary: Renewable wind power plays a growing role in the smart grid. Wind power forecasting is important due to the intermittent and fluctuating nature of wind. This paper proposes a self-attention-based neural network model for online learning, which captures the temporal relations in power sequences.
Article
Automation & Control Systems
Da-Wei Zhang, Guo-Ping Liu
Summary: This research focuses on addressing the output tracking problem for networked high-order fully actuated systems under communication delays and external disturbances. A novel HOFA system model is applied to establish the dynamics of networked control systems, and a disturbance observer based HOFA predictive control approach is proposed. A Diophantine Equation is applied to establish an incremental HOFA prediction model, and a necessary and sufficient criterion is given to discuss the stability and tracking performance of closed-loop NHOFA systems. The availability of the proposed approach is demonstrated through simulated and experimental results.
Article
Engineering, Electrical & Electronic
Yi Yu, Guo-Ping Liu, Wenshan Hu
Summary: This paper proposes a distributed predictive secure control method based on blockchain protocol to address the communication constraints and cyber attacks in DC microgrids. Experimental tests on a PV-based DC microgrid hardware system demonstrate the effectiveness of the proposed control strategy.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Yi Yu, Guo-Ping Liu, Wenshan Hu
Summary: This paper focuses on the voltage tracking problem in DC microgrids with communication delays and packet losses. A coupled discrete microgrid model is developed to accurately compensate for these communication constraints. The proposed consensus-based proportional-integral predictive control strategy actively compensates for delays and dropouts. Sufficient and necessary conditions for voltage tracking are given, as well as stability and convergence analysis of the closed-loop microgrid system.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Automation & Control Systems
Chuanguo Chi, Dong Lin, Clara-Mihaela Ionescu, Guo-Ping Liu
Summary: This paper investigates the application of distributed sliding-mode cloud predictive control scheme in networked multi-agent control systems (NMACS). A sliding-mode cloud predictive control (SMCPC) scheme based on the cloud control system is designed. The scheme combines the advantages of variable structure control (VSC) of sliding-mode control (SMC) and the advantages of cloud predictive control (CPC) in handling network delays. The feasibility and applicability of the control scheme are verified through analysis and experiments.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Computer Science, Theory & Methods
Zhongcheng Lei, Hong Zhou, Wenshan Hu, Guo-Ping Liu
Summary: This paper explores a novel system constructed based on front-end and back-end separation, which allows concurrent interactive experiments for multiple users, enabling massive access to virtual experimentation and avoiding the need for advance booking or queuing.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Multidisciplinary Sciences
Zhongcheng Lei, Hong Zhou, Xiaoran Dai, Wenshan Hu, Guo-Ping Liu
Summary: This paper discusses the design and implementation of a digital twin DC-DC converter for monitoring and control. The results show that the digital twin can dynamically track the converter, detect and replace faulty controllers in real time.
NATURE COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Wei Chen, Zidong Wang, Hongli Dong, Jingfeng Mao, Guo-Ping Liu
Summary: This article discusses the privacy-preserving distributed economic dispatch problem of microgrids. A distributed optimization algorithm with a constant step size is proposed by combining decentralized exact first-order algorithm with the push-sum protocol to achieve privacy preservation. It is demonstrated through analysis that the scheme is effective in protecting privacy in various scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Shengwang Ye, Guo-Ping Liu, Wenshan Hu, Zhongcheng Lei
Summary: This article introduces an IoT-based solution to a multiagent system experimentation in NCSLab. The proposed solution offers abundant choices for MAS experiments with its compact architecture and multiple features such as online algorithm design and live video monitor. The effectiveness of the proposed controller and its configurable ability for MAS are demonstrated through web-based experiments.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
