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Xueliang Wang,Jianwei Xia,Na Zhang,Miao Yu,Xiaoxiao Guo 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1
This article deals with the dynamic event-triggered tracking control problem for nonlinear switched systems with uncertain nonlinearities. By combining neural network control technology, mode-dependent average dwell time (MDADT) switching rule and dynamic event-triggered strategy, a valid adaptive control scheme is established, which guarantees the boundedness of all signals in the resulting closed-loop system and the tracking error eventually converges to a small neighborhood of the origin under a class of switching signals with MDADT property. Unlike the existing tracking control schemes, the proposed dynamic event-triggered strategy reduce some unnecessary transmissions from controller to actuator and thus saving network resources better. Finally, the effectiveness of the proposed control design is verified by a numerical simulation.
Tianshu Xu,Jianwei Xia,Xiao-Na Song,Zhen Wang,Hua-Sheng Zhang 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
In this paper, the topic of sampled-data based dissipativity control for Takagi-Sugeno (T-S) fuzzy Markovian jump systems with incomplete transition rates and actuator saturation is addressed. First of all, by constructing an appropriate two-sided closed-loop function that captures the realistic information of sampling pattern, together with the free-matrix-based inequality approach, a sufficient condition is developed to ensure the considered systems to be strictly(Q,S,R)-γ-dissipative. Then, the corresponding mode-dependent sampled-data controllers are designed based on the given dissipativity condition. As a corollary, the controller design is presented for the system without disturbance. Furthermore, an optimization problem is investigated in order to maximize the domain of the attraction. Finally, simulation examples are offered to verify the feasibility of the results.
Event-triggered Extended Dissipative Control for Networked Singular Systems
Meiyu Li,Jianwei Xia,Junsheng Zhao,Huasheng Zhang,Hao Shen 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.1
In this paper, an event-triggered extended dissipative control problem for networked singular systems isinvestigated, where the extended dissipativity analysis unifies the H∞ performance, L2 −L∞ performance, passivity,(Q,S,R)-dissipativity in one framework. Under the event-triggered scheme, the closed-loop system is modeled asa time-delay system. Some sufficient conditions for extended dissipativity are developed and presented in terms oflinear matrix inequalities (LMIs). Then the design of the state feedback controller becomes a matter of solving aset of LMIs. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method.
Wenjing Yang,Jianwei Xia,Xiaoxiao Guo,Miao Yu,Na Zhang 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.5
In this paper, an adaptive decentralized event-triggered global performance control of a class of largescale strongly interconnected nonlinear systems with external disturbances is investigated. Firstly, the original performance constrained large-scale nonlinear system is transformed into an equivalent unconstrained nonlinear largescale system by barrier function transformation. Secondly, the additional assumptions of interconnect terms such as upper bound function and matching conditions are eliminated by using the inherent properties of Gaussian function. In addition, an event-triggered mechanism is designed to reduce unnecessary transfers between the controller and the actuator for better resource efficiency. It is shown that the proposed control schemes guarantee that all signals of the closed-loop system are bounded, and the output tracking error is always kept within the given boundary. Finally, a numerical system and a mass-spring damping system are taken as examples to verify the effectiveness of the proposed control method.
Jikai Wang,Xia Huang,Zhen Wang,Jianwei Xia,Hao Shen 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.11
This paper studies the exponential synchronization of chaotic delayed neural networks (CDNNs) under aperiodic sampled-data control. First, an aperiodic sampled-data controller with exponentially decaying gain is designed to enlarge the maximum sampling period and the maximum allowable delay while still preserving the stability of the closed-loop system. Then, a novel time-dependent Lyapunov functional that consists of the information of the exponential decay rate η is elaborately designed to analyze the stability of the closed-loop system instead of using the common “change of coordinates” method. With the aid of Lyapunov theory and some inequality techniques, the sufficient conditions are established to guarantee the exponential synchronization of master-slave CDNNs. Based on matrix transformation, the equivalent conditions in LMI form are established to design the feedback gain. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed controller and the obtained synchronization criteria.
An Improved Result on Stability Analysis of Delayed Load Frequency Control Power Systems
Shiyu Jiao,Jianwei Xia,Zhen Wang,Xiangyong Chen,Jing Wang,Hao Shen 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4
This paper investigates the stability of power systems with load frequency control considering time delays(constant and time-varying delays). A new criterion for ensuring the stability of the system is proposed on the basisof Lyapunov stability theory and a further strengthened inequality. Finally, taking a single-area load frequencycontrol scheme with the proportional-integral controller as an example, according to the stability criterion obtained,the relationship between the maximum allowable delay and the gain of proportional-integral controller is discussed. Besides, in case studies, the effectiveness of our method is also demonstrated.
Robust Finite-time Extended Dissipative Control for a Class of Uncertain Switched Delay Systems
Hui Gao,Jianwei Xia,Guangming Zhuang 제어·로봇·시스템학회 2018 International Journal of Control, Automation, and Vol.16 No.3
This paper investigates the problem of finite-time extended dissipative analysis and control for a class of uncertain switched time delay systems, where the uncertainties satisfy the polytopic form. By using the average dwell-time and linear matrix inequality technique, some sufficient conditions are proposed to guarantee that the switched system is finite-time bounded and has finite-time extended dissipative performance, where the H∞, L2-L∞, Passivity and (Q, S, R)-dissipativity performance can be solved simultaneously in a unified framework based on the concept of extended dissipative. Furthermore, a state feedback controller is presented to guarantee that the closedloop system is finite-time bounded and satisfies the extended dissipative performance. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method.
Chenglong Zhu,Baomin Li,Jianwei Xia,Na Zhang,Rui Liu 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.6
In this paper, an adaptive event-triggered asymptotic tracking control problem is addressed for switched nonlinear systems with unknown control directions. In existing control schemes, the proposed controller is not directly aimed at the original system, which affects the control performance. Different from the existing control schemes, based on the original system, an event-triggered control law is constructed in this paper. The proposed event-triggered controller guarantees that the tracking error ς1 asymptotically converges to the origin. Finally, the effectiveness of the proposed controller design scheme is proved by simulation examples.
Minghe Li,Saifei Hu,Jianwei Xia,Jing Wang,Xiao-Na Song,Hao Shen 제어·로봇·시스템학회 2020 International Journal of Control, Automation, and Vol.18 No.9
In this work, the problem of predictive control of dissolved oxygen for the activated sludge process model with high nonlinearity and strong coupling is addressed. Firstly, the determination of the structure of fuzzy rules is displayed established upon Activated sludge model 1 (ASM1). Besides, the fuzzy space is divided through the clustering algorithm of fuzzy C-means. The corresponding parameters are estimated by means of the wellknown least squares method. Subsequently, a fuzzy predictive model of dissolved oxygen is established by using the historical data. The aim is to design a predictive controller that is capable of performing the online track of dissolved oxygen attributed to better dynamic response and steadier output in different weather. Ultimately, the availability and validity of the developed technique are verified by a comparison example.