International Journal of Robust and Nonlinear Control最新文献_第3页

Neural-Network-Based Adaptive Control of Time-Delayed Non-Linear Cyber-Physical Systems With Power Uncertainty Against Deception Attacks

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-30 DOI: 10.1002/rnc.7796

Jiakang Liang, Yadong Yang, Jiyu Zhu, Qikun Shen

{"title":"Neural-Network-Based Adaptive Control of Time-Delayed Non-Linear Cyber-Physical Systems With Power Uncertainty Against Deception Attacks","authors":"Jiakang Liang, Yadong Yang, Jiyu Zhu, Qikun Shen","doi":"10.1002/rnc.7796","DOIUrl":"https://doi.org/10.1002/rnc.7796","url":null,"abstract":"<div>\u0000 \u0000 <p>At this job, the adaptive control problem is investigated for a class of non-linear cyber-physical systems (CPSs), where the CPSs considered are not only subject to deception attacks and time delay, but also contain uncertain input powers. The deception attacks result in the actual values of the system state being unavailable and control gains being unknown. On the basis of the theory of Lyapunov stability, a new adaptive neural-networks-based control scheme is designed to guarantee the stability of the closed-loop system and mitigate the impact of deception attacks. Compared with the existing works in literature, (1) the input powers of the CPSs considered in this article are unknown and new controllers are constructed based on the neural network approximation technique; (2) the influence of unknown time delay is eliminated by using a novel Lyapunov–Krasovskii function. Furthermore, in order to address unknown gains caused by deception attacks, the Nussbaum gain technique is firstly extended to the CPSs with power uncertainties. Finally, the simulation results confirm the effectiveness of the control strategy presented in this work.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2288-2299"},"PeriodicalIF":3.2,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-Triggered Synchronization Control for Markov Jump Neural Networks With Partially Unknown Transition Probabilities

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-30 DOI: 10.1002/rnc.7781

Cheng Fan, Lei Su, Kang Wang, Xihong Fei

引用次数: 0

Decentralized Periodic Event-Triggered Control for Nonlinear Switched Systems

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-27 DOI: 10.1002/rnc.7803

Anqi Fu, Yongji Dai, Junfei Qiao

{"title":"Decentralized Periodic Event-Triggered Control for Nonlinear Switched Systems","authors":"Anqi Fu, Yongji Dai, Junfei Qiao","doi":"10.1002/rnc.7803","DOIUrl":"https://doi.org/10.1002/rnc.7803","url":null,"abstract":"<div>\u0000 \u0000 <p>Decentralized periodic event-triggered control (DPETC) is a method that allows sensors to be placed flexibly while cutting down on their workload and the amount of data they send in a feedback loop, which makes it a good fit for wireless network control systems. In this article, we investigate the control issues of nonlinear switched systems whose switches are determined by the system input and consider their stability by designing a DPETC scheme. Additionally, we model and control a water distribution system with looped pipe network using a switched model and the proposed theory. In this DPETC, at each periodic sampling time, the local event-triggered mechanism determines events by assessing whether the local sampling error meets the predefined triggering condition. If so, the collected sampling data will be transmitted to a central controller. This controller processes the data to compute the control input, with those nodes without events using the previous updated sampling data. Based on the derived control input, the controller then switches to the appropriate mode following the system's switches. The feasibility of the proposed method is demonstrated through three examples, including a smart water distribution system with looped pipeline.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2367-2382"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Consensus Control for Multiple Euler–Lagrange Systems With External Disturbances Based on Event-Triggered Communication

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-27 DOI: 10.1002/rnc.7786

Zhengqing Shi, Bo Li, Chuan Zhou, Jian Guo

{"title":"Robust Consensus Control for Multiple Euler–Lagrange Systems With External Disturbances Based on Event-Triggered Communication","authors":"Zhengqing Shi, Bo Li, Chuan Zhou, Jian Guo","doi":"10.1002/rnc.7786","DOIUrl":"https://doi.org/10.1002/rnc.7786","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, a novel robust consensus control protocol is proposed for multiple uncertain Euler–Lagrange systems with unknown external disturbances. First, the local adaptive control laws are derived under event-triggered communication framework, and the robust consensus control problem is transformed into an equivalent optimal control problem with disturbance rejection. Event-triggered mechanisms and distributed state estimators are designed by utilizing only triggered exchanging states, by which continuous monitoring neighbors' states is avoided and communication burdens are effectively reduced. Second, the Hamilton–Jacobi–Isaac equations are formulated based on zero-sum differential game theory, and adaptive dynamic programming methods are employed to approximate the Nash-equivalent solutions, by which the local robust optimal control laws are derived to eliminate the disturbance effects and improve the robustness of the proposed strategy. It is strictly proved that all signals in the closed-loop systems are uniformly ultimately bounded and the cost functions are minimized. Finally, two practical examples are presented to validate the proposed strategy.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2170-2183"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Parameter Estimate and Adaptive Control of DARMA Systems With Uniform Quantized Output Data

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-27 DOI: 10.1002/rnc.7769

Lida Jing

引用次数: 0

A Novel Dual-Loop Model-Free Adaptive Iterative Learning Control and Its Application to the Refrigeration Systems

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-27 DOI: 10.1002/rnc.7790

Nasreldin Ibrahim, Na Dong

{"title":"A Novel Dual-Loop Model-Free Adaptive Iterative Learning Control and Its Application to the Refrigeration Systems","authors":"Nasreldin Ibrahim, Na Dong","doi":"10.1002/rnc.7790","DOIUrl":"https://doi.org/10.1002/rnc.7790","url":null,"abstract":"<div>\u0000 \u0000 <p>This study investigates a novel dual-input and dual-output Model-Free Adaptive Iterative Learning Control (A-MFAILC) approach for energy-saving control of refrigeration systems, aiming to maintain a minimum stable superheat and a constant evaporation temperature. Superheat control is often unstable due to the complex and high-order nature of refrigeration systems. Furthermore, these systems often face large time delays, which complicate the tracking control process. Such delays can cause inefficiencies and instability in maintaining desired operational parameters, making it challenging to achieve energy savings. To get around these problems, a novel Model-Free Adaptive Iterative Learning Control algorithm has been proposed by incorporating input rate constraints for time-delayed systems.The proposed A-MFAILC algorithm with a single input and single output has been extended to dual input and dual output energy-saving control of refrigeration systems. Complete proofs of convergence analysis have been provided, and the algorithm's performance has been fully evaluated. Simulation tests based on the proposed A-MFAILC algorithm, developed for dual-loop control systems, have been conducted on refrigeration systems. Step signals have been used as input signals for comprehensive performance testing. As a result, the proposed approach demonstrates higher tracking stability and fast response speed, with an average tracking accuracy of 98.68% and 93.87% for superheat and evaporation temperature, respectively.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2213-2234"},"PeriodicalIF":3.2,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intermittent Dynamic Event-Triggered Optimal Control for Networked Control Systems With Input Saturation

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-26 DOI: 10.1002/rnc.7767

Cong Zhang, Xiaodan Zhang, Feng Xiao, Bo Wei

{"title":"Intermittent Dynamic Event-Triggered Optimal Control for Networked Control Systems With Input Saturation","authors":"Cong Zhang, Xiaodan Zhang, Feng Xiao, Bo Wei","doi":"10.1002/rnc.7767","DOIUrl":"https://doi.org/10.1002/rnc.7767","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, we explore an event-triggered optimal control problem for nonlinear networked control systems (NCSs) with input saturation and aperiodic intermittent control. First, a non-quadratic cost function with the property of intermittent control is formulated, and a Hamilton-Jacobi-Bellman (HJB) equation is designed based on the given cost function to acquire optimal control inputs. To avoid continuous-time communication in networks, a novel aperiodically intermittent dynamic event-triggered (AIDET) control scheme, integrating a dynamic event-triggered control scheme and an aperiodic intermittent control scheme, is proposed in this article. A piecewise continuous internal dynamic variable is introduced in the event-triggering condition, which is more conducive to increasing inter-event times than static event-triggering schemes. Furthermore, the event-triggering condition designed in this article is proven strictly to exclude the Zeno behavior. Moreover, due to the difficulty of directly solving the HJB equation, an actor-critic algorithm in the AIDET scheme is proposed to approximate the optimal control inputs. The approximation errors of weight vectors are proved to be uniformly ultimately bounded. The stability of the considered systems in the proposed AIDET control scheme is analyzed using the Lyapunov theory. Finally, some simulation examples are given to illustrate the effectiveness of the proposed actor-critic algorithm-based AIDET control scheme.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"1935-1949"},"PeriodicalIF":3.2,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Triggered Distributed Model Predictive Control via Path Parameter Synchronization

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-26 DOI: 10.1002/rnc.7773

Qianqian Chen, Shaoyuan Li

{"title":"Self-Triggered Distributed Model Predictive Control via Path Parameter Synchronization","authors":"Qianqian Chen, Shaoyuan Li","doi":"10.1002/rnc.7773","DOIUrl":"https://doi.org/10.1002/rnc.7773","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the formation tracking problem for multiple mobile robots via self-triggered distributed model predictive control (DMPC) strategy and path-parameter communication manner. To ensure the robots follow the desired formation structure along the predefined paths, we establish appropriate tracking error models that form a multi-agent system. At triggered instants, each agent exchanges a sequence of path parameters representing the robot's position, resolves the optimal control problem (OCP) and subsequently determines the open-loop phase. Different from existing coordination methodology, the proposed scheme exhibits two essential merits in environments where resources are particularly limited: (1) The tracking task of robots is achieved by designing an appropriate OCP under the DMPC scheme, and the formation task of robots is achieved through the synchronization of one-dimensional path parameters instead of the multi-dimensional state information, which demands less communication load; (2) The incorporation of the self-triggered scheduler acquires the desired control performance with less calculation time, thereby relieving the computational and communication costs. Sufficient conditions are proposed to guarantee the recursive feasibility of the OCP and the closed-loop stability. Simulation results illustrate the validity of the proposed control algorithm.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2027-2042"},"PeriodicalIF":3.2,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143582008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Fuzzy Fault-Tolerant Control for CSTR With State Constraints Dependent on Temperature and Concentration

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-25 DOI: 10.1002/rnc.7782

Yinqiao Ma, Lei Liu, Dapeng Li, Dongjuan Li

{"title":"Adaptive Fuzzy Fault-Tolerant Control for CSTR With State Constraints Dependent on Temperature and Concentration","authors":"Yinqiao Ma, Lei Liu, Dapeng Li, Dongjuan Li","doi":"10.1002/rnc.7782","DOIUrl":"https://doi.org/10.1002/rnc.7782","url":null,"abstract":"<div>\u0000 \u0000 <p>The indispensable experimental equipment of the continuous stirred tank reactor (CSTR) is crucial in chemical production processes. This paper presents a novel adaptive state-dependent constraint control method for nonlinear CSTR system. The CSTR system is transformed into the nonlinear system with a pure feedback structure begins with the mean value theorem. Subsequently, the Fuzzy logic systems (FLS) is used to approximate unknown dynamics. Reactant concentration and mixture temperature are crucial variables in CSTR system. When these variables surpass the specified constraints, it can lead to a decrease in product quality and yield. The constraint boundaries considered in this paper are dependent on both state and time. Therefore, the time-varying asymmetric Barrier Lyapunov Function (BLF) is proposed to deal with state-dependent constraints. Additionally, the actuator fault is resolved in this paper, by considering fault-tolerant control strategy. Lyapunov stability analysis shows that all signals in a closed-loop system are bounded. Finally, the effectiveness of the control scheme is verified by the simulation of CSTR system.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2119-2129"},"PeriodicalIF":3.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Iterative Learning Model Predictive Control for Nonlinear Batch Processes

IF 3.2 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2024-12-25 DOI: 10.1002/rnc.7783

Chengyu Zhou, Li Jia, Jianfang Li

{"title":"Improved Iterative Learning Model Predictive Control for Nonlinear Batch Processes","authors":"Chengyu Zhou, Li Jia, Jianfang Li","doi":"10.1002/rnc.7783","DOIUrl":"https://doi.org/10.1002/rnc.7783","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper once again focuses on the research of iterative learning model predictive control (ILMPC) in batch processes, which aims to ensure that the system has fast convergence speed and good non-repetitive disturbance suppression ability. Firstly, using the process input and output data, a nonlinear batch process composite model consisting of a nominal ARX model and a JITL model is established, where the former is used to describe the process dynamics and the latter to evaluate the modeling error caused by the process nonlinearity. Then, an improved ILMPC (IILMPC) method is proposed, which considers the current iteration input, the input increment along the iteration axis, and the input increment in the time axis in an integrated two-dimensional feedback design framework. Meanwhile, a slack variable is also taken into account in the IILMPC design algorithm to ensure that a feasible solution will always exist. These advantages drive the presented control strategy to give better tracking performance than existing ILMPC. The convergence of the IILMPC algorithm is analyzed under mild conditions. Finally, a simulation case is given to verify the effectiveness of the proposed control method.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 6","pages":"2130-2141"},"PeriodicalIF":3.2,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143581962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0