Article
Automation & Control Systems
Shunchao Zhang, Bo Zhao, Derong Liu, Cesare Alippi, Yongwei Zhang
Summary: In this article, an event-triggered robust control (ETRC) method is investigated for multi-player nonzero-sum games of continuous-time input constrained nonlinear systems with mismatched uncertainties. The method transforms the robust control problem into an optimal regulation problem by constructing an auxiliary system and designing an appropriate value function. A critic neural network (NN) is used to approximate the value function of each player and obtain control laws. The method reduces computational burden and communication bandwidth by updating the control laws when events occur. The effectiveness of the developed ETRC method is demonstrated through theoretical analysis and examples.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Qing Geng, Haobin Ma, Li Li
Summary: This article proposes an event-triggering mechanism (ETM)-based security control strategy for an uncertain networked control system (NCS) to deal with jamming attacks. The article constructs a system control block structure for the attacked uncertain NCS and designs a virtual system to handle mismatched parametric uncertainty. It also engineers an optimal jamming attack strategy and an ETM-based control strategy with jamming parameters to ensure the stability of the NCS under uncertainty and jamming attacks.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Ping Wang, Zhen Wang, Qian Ma
Summary: This paper proposes an event-triggered optimal control strategy based on adaptive dynamic programming (ADP) for constrained continuous-time nonlinear systems. It introduces a novel event-triggering condition to guarantee the stability of the closed-loop system and proves the existence of a lower bound for the execution time to avoid Zeno behavior. A critic Neural Network (NN) is designed to approximate the cost function and solve the partial differential Hamilton-Jacobi-Bellman (HJB) equation, leading to the ADP-based ETOC scheme. Through Lyapunov stability analysis, the stability of the closed-loop system is ensured, along with guaranteed uniform ultimate boundedness of the states and weight estimation error.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2022)
Article
Automation & Control Systems
Kexue Zhang, Elena Braverman, Bahman Gharesifard
Summary: This study focuses on event-triggered control of nonlinear discrete-time systems with time delays. A novel event triggered control algorithm is proposed based on a Lyapunov-Krasovskii type input-to-state stability result. The algorithm updates the control inputs only when a certain measurement error surpasses a dynamical threshold. Sufficient conditions are established to ensure the asymptotic stability of the closed-loop system.
Article
Computer Science, Artificial Intelligence
Wenqi Xu, Xiaoping Liu, Huanqing Wang, Yucheng Zhou
Summary: This article presents a novel event-based adaptive neural network control algorithm for MIMO nonlinear discrete-time systems. The designed controller avoids dependence on virtual controls and only requires system states, reducing computational burden and simplifying algorithm implementation. Radial basis function NNs are used to approximate control input and the Lyapunov difference approach ensures semiglobal uniformly ultimate boundedness of all signals in the closed-loop system. The effectiveness of the algorithm is demonstrated through a simulation example.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Mathematics, Applied
Xingling Shao, Xiaohui Yue, Jie Li
Summary: An event-triggered robust control scheme for quadrotors with preassigned time performance constraints is proposed in this study. By incorporating switching threshold event-triggered strategy and extended state observers, real-time estimation and time performance control are achieved while maintaining stability and efficiency.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Automation & Control Systems
Xiumei Han, Xudong Zhao, Tao Sun, Yuhu Wu, Ning Xu, Guangdeng Zong
Summary: This article examines the problem of event-triggered optimal control for discrete-time switched nonlinear systems with constrained control input, proposing a novel method called event-triggered heuristic dynamic programming (ETHDP) to derive optimal control policies effectively. The use of two neural networks helps decrease calculation and transmission load when the event-triggered condition is violated. The convergence of ETHDP is proven and the proposed method's effectiveness is verified through an example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yixuan Wang, Hui Gao, Yang Yang, Pan Xu
Summary: In this paper, we propose a multi-thread control algorithm based on an event-triggered mechanism to solve the control problem for systems with a mismatch between the number of controllers and plants. The algorithm ensures input-to-state stability and the ability to save communication and computing resources. Simulations demonstrate its flexibility, robustness, and practicability.
Article
Mathematics
Quanyu Bai, Wei Zhu
Summary: This paper investigates the event-triggered impulsive optimal control for linear continuous-time dynamic systems. It presents an optimal feedback controller with input time-delay, where the impulsive instants are determined by a designed event-triggering function and condition depending on the system state. Some sufficient conditions are given to ensure exponential stability with the optimal controller. Additionally, the Zeno-behavior for the impulsive instants is excluded. The validity of the theoretical results is verified through a numerical simulation example.
Article
Engineering, Mechanical
Shanlin Liu, Ben Niu, Guangdeng Zong, Xudong Zhao, Ning Xu
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
Engineering, Mechanical
Tong Hua, Jiang-Wen Xiao, Xiao-Kang Liu, Yan Lei, Yan-Wu Wang
Summary: This paper investigates the event-triggered sub-optimal control problem for two-time-scale systems with unknown slow dynamics. A composite event-triggered optimal controller design is proposed for the decoupled slow and fast subsystems with different triggering conditions. The actor and critic networks are utilized to approximate the optimal controller employing tuning laws applied to the weights. The results demonstrate that the system employing the proposed event-triggered mechanism can achieve asymptotic stability and afford a sub-optimal controller.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Zhipei Hu, Peng Shi, Jin Zhang, Feiqi Deng
Summary: Event-triggered schemes are characterized by less communication traffic while maintaining the desired stability and performance criteria of the controlled system. This paper addresses modeling and control problems for a class of discrete-time stochastic systems with event-triggered schemes in the presence of packet dropouts. Two different mathematical analysis methods are proposed to model packet loss in event-triggered schemes, ensuring mean-square exponential stability and achieving the prescribed H-infinity performance level.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Yingjie Hu, Ding Fan, Kai Peng, Herbert Ho-Ching Iu, Xinan Zhang
Summary: The study presents a robust event-triggered model predictive control based on LMIs for discrete linear systems subject to disturbances. By setting the event-triggering mechanism, utilizing stability conditions, designing Lyapunov weight matrix and adopting dual-mode control, the proposed control strategy achieves control objectives and reduces computational complexity.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Computer Science, Artificial Intelligence
Zhihong Liang, Sanbo Ding, Yanhui Jing, Xiangpeng Xie
Summary: This paper studies the synchronization control of discrete-time complex dynamical networks under intermittent networked communication. A novel aperiodic intermittent event-triggered mechanism is proposed to save communication and computing resources. The concepts of average working time ratio and average working period are introduced to describe intermittent aperiodic performance. A sufficient criterion for the synchronization of discrete-time complex dynamical networks is obtained.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Information Systems
Menghua Chen
Summary: This paper discusses the issue of input-output finite-time stability (IO-FTS) for a class of nonlinear discrete time-varying systems and proposes a time-varying observer-based sliding mode control method. An adaptive event-triggered mechanism is proposed to mitigate the transmission burden. A time-varying Lyapunov functional is designed to consider the effect of time-delay phenomenon and time-varying system matrices. Sufficient conditions are established based on the designed Lyapunov functional and IO-FTS theory for the error estimation system and closed-loop state estimation system. Conditions in terms of recursive linear matrix inequalities (RLMIs) are obtained to ensure IO-FTS during both reaching phase and sliding mode phase. An algorithm is provided to solve the RLMIs and obtain the time-varying observer gains. The effectiveness and superiority of the proposed method is demonstrated through an industrial continuous-stirred tank reactor system.
Article
Automation & Control Systems
Sayan Basu Roy, Shubhendu Bhasin, Indra Narayan Kar
ASIAN JOURNAL OF CONTROL
(2020)
Article
Automation & Control Systems
Niraj Choudhary, Janardhanan Sivaramakrishnan, Indra Narayan Kar
INTERNATIONAL JOURNAL OF CONTROL
(2020)
Article
Engineering, Electrical & Electronic
M. M. Rayguru, I. N. Kar
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2020)
Article
Engineering, Aerospace
Rajasree Sarkar, Joyjit Mukherjee, Deepak Patil, Indra Narayan Kar
Summary: A Reusable Launch Vehicle (RLV) faces uncertain environment and extreme turbulence during the re-entry phase, requiring an effective control strategy for safe landing. A Time-Delayed Control (TDC) strategy has been proposed to track the space vehicle trajectory in the presence of uncertainties, with theoretical analysis confirming stability and simulation studies validating robust tracking of the optimal trajectory.
ADVANCES IN SPACE RESEARCH
(2021)
Article
Automation & Control Systems
Arunava Banerjee, Joyjit Mukherjee, Mashuq un Nabi, Indra Narayan Kar
Summary: This paper proposes an efficient guidance strategy for a two-dimensional interceptor problem, generating an near optimal trajectory using Differential Evolution and guiding the missile to intercept the target through robust control law.
Article
Energy & Fuels
Ganesh P. Prajapat, N. Senroy, I. N. Kar
Summary: An enhanced control strategy is proposed for the DFIG-based variable speed wind turbine system to maximize energy extraction from variable wind. The strategy modifies the reference torque to improve MPPT, utilizing estimated wind speed and unobservable states. The proposed approach acts during transient time, requires no alterations to existing control systems, and can be implemented in real-life applications without much additional cost.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Automation & Control Systems
Joyjit Mukherjee, Spandan Roy, Indra Narayan Kar, Sudipto Mukherjee
Summary: This article introduces an adaptive-robust maneuvering control framework for a planar snake robot to address parameter uncertainties. The control objective is to maintain consistent motion of the snake robot's body shape while tracking velocity and head angle simultaneously. The proposed dual adaptive-robust time-delayed control (ARTDC) demonstrates improved performance compared to existing methodologies in simulation studies.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Madan Mohan Rayguru, Bhabani Shankar Dey, Indra Narayan Kar
Summary: Contractive nonlinear systems have attracted attention from the control community due to their desirable properties. An extended HGO based output feedback strategy is proposed in this work, which ensures contraction of a class of uncertain singularly perturbed systems. The analysis shows that the smallness requirement of the singular perturbation parameter can be relaxed for certain classes of nonlinear systems, offering additional freedom to tune the closed loop performances.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Automation & Control Systems
Madan Mohan Rayguru, Spandan Roy, Indra Narayan Kar
Summary: This article presents a saturated tracking controller based on a different theoretical framework, ensuring bounded tracking performance and quantifying steady-state error bounds in multi-input-multi-output nonlinear systems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Rajasree Sarkar, Deepak Patil, Indra Narayan Kar
Summary: This study proposes an alternative strategy for solving the time-L-1 optimal control problem by intermittently applying open-loop optimal solution. The strategy retains system states within a small bounded safe region and achieves practical stability with reduced usage of system resources.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Article
Automation & Control Systems
Rajasree Sarkar, Deepak Patil, Ameer K. Mulla, Indra Narayan Kar
Summary: The computation of a decentralized feedback strategy for the consensus tracking problem of multi-agent systems is considered in this study. The agents can communicate over a directed graph and track the reference trajectory generated by the root node in finite time.
IEEE CONTROL SYSTEMS LETTERS
(2022)
Proceedings Paper
Automation & Control Systems
Rajasree Sarkar, Joyjit Mukherjee, Deepak Patil, Indra Narayan Kar
2020 28TH MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION (MED)
(2020)
Proceedings Paper
Automation & Control Systems
Shyam Krishan Joshi, Shaunak Sen, Indra Narayan Kar
Proceedings Paper
Automation & Control Systems
Sujeet Kumar, I. N. Kar
Article
Computer Science, Information Systems
Niladri Sekhar Tripathy, Indra Narayan Kar, Mohammadreza Chamanbaz, Roland Bouffanais