International Journal of Robust and Nonlinear Control最新文献

{"title":"A multilayer neural‐network‐based fault estimation and fault tolerant control scheme for uncertain system","authors":"Zainab Akhtar, Syed Zilqurnain Abbas Naqvi, Mirza Tariq Hamayun, Salman Ijaz","doi":"10.1002/rnc.7604","DOIUrl":"https://doi.org/10.1002/rnc.7604","url":null,"abstract":"This work introduces a new actuator fault estimation approach coupled with a fault‐tolerant control (FTC) strategy for uncertain systems in an output feedback framework. The proposed method involves constructing a Multi‐Layer Neural Network (MLNN) observer‐based fault estimation unit to accurately predict system states and potential faults in the actuator channel. An online control allocation (CA) scheme is then developed, utilizing the derived estimates to actively reconfigure the virtual control signals among the healthy redundant actuators in the event of actuator malfunction. Furthermore, an adaptive neural network‐based output integral sliding mode control scheme is designed based on the virtual control. This integration enhances the overall system's robustness and significantly reduces the chattering effect. The stability analysis of the proposed fault estimations scheme is initially performed using MLNN structure, followed by a comprehensive closed‐loop stability analysis to establish the stability of the entire system. Finally, the effectiveness of the proposed method is validated on a nonlinear six‐degree‐of‐freedom model of multirotor unmanned aerial vehicle aircraft. Numerical simulations under different fault and failure scenarios validate the efficacy of the proposed method. The comparative analysis of the proposed scheme is conducted with the static output feedback control allocations and adaptive allocation strategy. This analysis focuses on evaluating performance using metrics such as root mean square error and mean square deviation, particularly in the presence of faults and failures. The results demonstrate the superior performance of the proposed scheme in fault/failure conditions.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"274 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214579","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}

{"title":"Fixed‐time rotating consensus control of second‐order multi‐agent systems","authors":"Liwei Kou, Yi Huang, Guangyu Zuo, Long Jian, Yinke Dou","doi":"10.1002/rnc.7607","DOIUrl":"https://doi.org/10.1002/rnc.7607","url":null,"abstract":"This article investigates the fixed‐time rotating consensus problem of second‐order multi‐agent systems in both the leaderless and leader‐following cases. Specifically, in the leaderless case, a distributed controller is developed to drive all agents to reach rotating consensus in fixed‐time. In the leader‐following case, a distributed fixed‐time observer is first proposed to estimate the position of a rotating leader. Then, a local fixed‐time output feedback controller without any velocity measurements is proposed to achieve the leader‐following motion. Furthermore, an integral sliding mode control technique is applied to handle the case where the multi‐agent system is subject to time varying external disturbances. Based on the bi‐limit homogeneity method and Lyapunov theory, we prove that all the agents reach the rotating consensus within a fixed time independent of initial conditions. Finally, simulations illustrate the effectiveness of the proposed controllers.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"62 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226877","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}

{"title":"An optimization-based method for robust stabilization of linear delay systems","authors":"Renhong Hu,&nbsp;Jie Mei,&nbsp;Guangfu Ma","doi":"10.1002/rnc.7603","DOIUrl":"10.1002/rnc.7603","url":null,"abstract":"<p>This paper investigates the robust stabilization problem of linear delay systems with parametric uncertainty. First, by means of the argument principle, a delay-dependent sufficient condition is derived for designing a feedback controller, with which the closed-loop system can achieve robust stability. Then, based on the fundamental matrix of the linear delay systems, a constrained optimization problem is formulated for solving the feedback gain matrices. The effectiveness of the proposed method is verified by some simulation results.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"34 17","pages":"11416-11431"},"PeriodicalIF":3.2,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214576","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}

{"title":"Practical time‐varying formation cooperative control for high‐order nonlinear multi‐agent systems avoiding spatial resource conflict via safety constraints","authors":"Xiaoshan Ma, Tawei Chou","doi":"10.1002/rnc.7600","DOIUrl":"https://doi.org/10.1002/rnc.7600","url":null,"abstract":"The operation of multi‐agent systems (MAS) in space necessitates considerations for obstacle avoidance, collision prevention, and connectivity among agents. This coupling conflict, stemming from spatial resource utilization, poses a significant and non‐negligible threat to the safe operation of MAS. This article proposes a consensus control scheme for the time‐varying formation of MAS, incorporating functions for maintaining connectivity, collision avoidance, and obstacle dodging. This scheme effectively constrains the time‐varying formation tracking error within an arbitrarily small range. The considered system model takes a high‐order nonlinear form, with uncertainties and disturbances present in each order. This grants the control scheme with high generality and practicability. By employing barrier Lyapunov function to delineate the safe operational space of MAS, conflicts in spatial resource utilization are avoided. This approach simultaneously fulfills the requirements for connectivity maintenance, collision avoidance, and obstacle dodging in the safe operation of MAS. An additional rotation operator is integrated into the controller to smoothly address the “minima” problem, eliminating the need for external intervention. Gaussian radial basis function is used to estimate the nonlinear terms, uncertainties, and unknown perturbation online in the system. The stability of the MAS under the proposed control scheme is analyzed through Lyapunov function. Finally, numerical simulation results are demonstrated to explain the effectiveness of the control scheme.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"124 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214626","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}

{"title":"Robustness of higher-order network pertinent to first- and higher-order dependency","authors":"Cuiping Ren,&nbsp;Bianbian Chen,&nbsp;Fengjie Xie","doi":"10.1002/rnc.7594","DOIUrl":"10.1002/rnc.7594","url":null,"abstract":"<p>Robustness of higher-order network (HON) with dependency is different from first-order network (FON), as the attack orders and the number of iterations are totally different. To measure the robustness of HON with dependency, this study proposed new attack strategies on node and edge failure through measuring the size of the giant component and global efficiency. And two real-world systems of hazardous materials transportation accident causation system and Chinese high-speed railway system with different network size were empirically studied. Results show that HON is more fragile to robustness attacks than FON. The number of attack iterations is uncertain in HON, which depends on the attack strategies and the network structure. Meanwhile, nodes and edges with high dependency have greater impacts on network robustness, providing valuable insights into capturing critical information. This study may be helpful to design the robust system, improve the system's reliability and serve as a valuable reference for future exploration of HONs robustness.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"34 17","pages":"11804-11818"},"PeriodicalIF":3.2,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214575","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}

{"title":"Event‐triggered adaptive neural network‐based optimal control of strictly feedback switched nonlinear systems with state constraints","authors":"Jie Ruan, Yuhui Fu, Yuan Fan","doi":"10.1002/rnc.7602","DOIUrl":"https://doi.org/10.1002/rnc.7602","url":null,"abstract":"In this article, we present an innovative approach for controlling nonlinear switched systems (NSSs) with strict feedback utilizing adaptive neural networks (ANNs). Our methodology encompasses several facets, addressing key challenges inherent to these systems. To commence, we tackle the constrained nature of NSSs with strict feedback by designing a barrier Lyapunov function. This function ensures that all states within the switched systems remain within prescribed constraints. Additionally, we harness neural networks (NNs) to approximate the unknown nonlinear functions inherent to the system. Furthermore, we deploy an ANN state observer to estimate unmeasurable states. Our approach then proceeds to develop a cost function for the subsystem. Building upon this, we apply the Hamiltonian–Jacobi–Bellman (HJB) solution in conjunction with observer and behavior critic architectures, all rooted in backstepping control (BC) principles. This integration yields both a virtual optimal controller and a real optimal controller. Furthermore, we introduce a novel ANN event‐triggered control (ETC) strategy tailored explicitly for strictly feedback systems. This strategy proves highly effective in reducing the utilization of communication resources and eliminating the occurrence of Zeno behavior. Our analysis provides formal proof that all states within the closed‐loop system exhibit half‐leaf consistency and are ultimately bounded, regardless of arbitrary switching conditions. Finally, we substantiate the efficacy and viability of our control scheme through comprehensive numerical simulations.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"6 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214580","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}

{"title":"Graphical tuning method of PID controller for systems with uncertain parameters based on affine algorithm","authors":"Minghui Chu","doi":"10.1002/rnc.7614","DOIUrl":"https://doi.org/10.1002/rnc.7614","url":null,"abstract":"For systems with uncertain parameters, it is very important to find a controller that can satisfy the preset robustness. The traditional method often ignores the influence of parameter coupling on the set boundary system when substituting the original system with the boundary system group, resulting in the calculated controller value region being too conservative. In this article, noise information is introduced based on affine algorithm to describe uncertain system parameters. Then, based on Kharitonov theorem, a new grouping method for boundary systems is proposed. This method takes the parameter coupling information into account when determining the boundary system, and avoids the problem of interval conservation. On this basis, a virtual phase margin tester is introduced to ensure that the obtained controller parameter range can make the system meet the specific robustness requirements. The results obtained in this article are general and strictly proved. Finally, examples are provided to illustrate the design process and verify the feasibility and efficacy of the proposed approach.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"7 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226879","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}

{"title":"Event‐triggered tracking control for networked control systems under diversified attacks","authors":"Jie Cao, Zeyu Yang, Shifang Dai, Jinliang Liu, Lijuan Zha","doi":"10.1002/rnc.7616","DOIUrl":"https://doi.org/10.1002/rnc.7616","url":null,"abstract":"This paper mainly concerns on the tracking control problem for event‐triggered networked control systems (NCSs) with diversified cyber‐attacks. An event‐triggered mechanism (ETM) is exploited to decrease the amount of redundant transmissions, thus saving communication resources. In addition, a novel tracking error model for NCSs is built with consideration of ETM and diversified cyber‐attacks, which involves deception attacks and Denial‐of‐Service (DoS) attacks. On the basis of Lyapunov stability theory and linear matrix inequalities (LMIs), the stability criterion of the tracking error system is constructed, and the controller is designed to ensure the tracking performance of the system. In the end, simulation examples are provided to testify the validity of the proposed method.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"8 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226878","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}

{"title":"Neural learning control for sampled‐data nonlinear systems based on Euler approximation and first‐order filter","authors":"Dengxiang Liang, Min Wang","doi":"10.1002/rnc.7609","DOIUrl":"https://doi.org/10.1002/rnc.7609","url":null,"abstract":"The primary focus of this research paper is to explore the realm of dynamic learning in sampled‐data strict‐feedback nonlinear systems (SFNSs) by leveraging the capabilities of radial basis function (RBF) neural networks (NNs) under the framework of adaptive control. First, the exact discrete‐time model of the continuous‐time system is expressed as an Euler strict‐feedback model with a sampling approximation error. We provide the consistency condition that establishes the relationship between the exact model and the Euler model with meticulous detail. Meanwhile, a novel lemma is derived to show the stability condition of a digital first‐order filter. To address the non‐causality issues of SFNSs with sampling approximation error and the input data dimension explosion of NNs, the auxiliary digital first‐order filter and backstepping technology are combined to propose an adaptive neural dynamic surface control (ANDSC) scheme. Such a scheme avoids the ‐step time delays associated with the existing NN updating laws derived by the common ‐step predictor technology. A rigorous recursion method is employed to provide a comprehensive verification of the stability, guaranteeing its overall performance and dependability. Following that, the NN weight error systems are systematically decomposed into a sequence of linear time‐varying subsystems, allowing for a more detailed analysis and understanding. In order to ensure the recurrent nature of the input variables, a recursive design is employed, thereby satisfying the partial persistent excitation condition specifically designed for the RBF NNs. Meanwhile, it can verify that the NN estimated weights converge to their ideal values. Compared with the common ‐step predictor technology, there is no need to redesign the learning rules due to the designed NN weight updating laws without time delays. Subsequently, after capturing and storing the convergence weights, a novel neural learning dynamic surface control (NLDSC) scheme is specifically formulated by leveraging the acquired knowledge. The introduced methodology reduces computational complexity and facilitates practical implementation. Finally, empirical evidence obtained from simulation experiments validates the efficacy and viability of the proposed methodology.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"34 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227835","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}

{"title":"Velocity‐free attitude coordination control of multiple rigid spacecraft with practical predefined‐time convergence","authors":"An‐Min Zou, Yanling Tang, Xinran Yu, Dexin Jiao","doi":"10.1002/rnc.7610","DOIUrl":"https://doi.org/10.1002/rnc.7610","url":null,"abstract":"The issue of velocity‐free practical predefined‐time (PPT) attitude coordination control (ACC) for multiple rigid spacecraft under directed topology and subject to bounded external disturbances is investigated in the article. To gain precise estimates of the spacecraft's velocities together with external disturbances, PPT extended‐state observers are presented by virtue of a time‐varying function technique. Next, distributed PPT state observers are designed to estimate the leader's attitude which is accessible to only some of the followers. One advantage of the designed distributed observers is that the information required to transmit among neighbor spacecraft is only the estimated attitudes, which results in a reduction of the communication burden. Then, a distributed velocity‐free PPT ACC law is put forward in terms of the backstepping approach and the PPT observers. The present control protocol can ensure that the settling time is bounded by a predefined time with no reliance on any other controller parameters or initial conditions. Finally, the efficiency of the developed ACC scheme is illustrated by numerical simulation examples, and it is shown that the designed control law possesses one further salient advantage of required reduced magnitudes of control torques to reach accurate ACC performance.","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"78 2 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142214616","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}