International Journal of Robust and Nonlinear Control最新文献

{"title":"An Iterative Approach for Self-Triggered Control of Linear Systems Based on a Hierarchical Cooperation Framework","authors":"Chenyang Wang,&nbsp;Haiying Wan,&nbsp;Xiaoli Luan,&nbsp;Hamid Reza Karimi,&nbsp;Fei Liu","doi":"10.1002/rnc.8063","DOIUrl":"https://doi.org/10.1002/rnc.8063","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we propose a self-triggered control mechanism based on a hierarchical strategy for linear systems which can further save computer resources while ensuring the advantages of the traditional self-triggered strategy. A hierarchical cooperation framework is developed to optimize the control structure in the design of the controller, with the upper layer calculating the inter-execution intervals and the lower layer computing the control input. To improve the system performance, we introduce an alternating solution strategy for iteratively deriving the next sampling instant and input. The one-step finite horizon boundary is applied to compute the initial triggering interval. Within each subsequent triggering interval, the control input values are determined by minimizing the specified performance index in the lower controller. These values are then fed back to the upper trigger for the calculation of the next triggering interval, on the premise of ensuring the system's stability. By fostering collaboration between control and triggering mechanisms and facilitating iterative optimization across different levels, the number of system triggers is significantly reduced, and the convergence speed of state trajectory is accelerated. The efficiency and superiority of the proposed method are demonstrated through a numerical simulation example.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6485-6494"},"PeriodicalIF":3.2,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145100952","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 Iterative Learning Control of Regular Time-Varying Multi-Agent Systems Under Switching Topology","authors":"Wei Cao,&nbsp;Huanhuan Li,&nbsp;Jinjie Qiao,&nbsp;Yi Zhu","doi":"10.1002/rnc.8062","DOIUrl":"https://doi.org/10.1002/rnc.8062","url":null,"abstract":"<div>\u0000 \u0000 <p>An event-triggered iterative learning control algorithm is proposed to address the consensus problem of regular time-varying multi-agent systems under switching topology, while considering the insufficient resource space of the system and the output saturation constraint phenomenon. Firstly, the algorithm utilizes the pseudo partial derivative estimates and output estimation errors to design an output observer to overcome the output constrained in the communication network. Secondly, the output estimation error of the observer and the trigger function are used to design the event trigger condition, and when the trigger function value satisfies the event trigger condition, the state values of the agents are updated; otherwise, the state values of the agents will remain unchanged. The gain error of the output observer is used as a variable to design the deadband controller function to avoid the Zeno phenomenon effectively. Then, the control algorithm utilizes the pseudo partial derivative estimation value to adjust the proportion of consistency error in real time, thereby continuously correcting the control input. Under the condition that both the pseudo partial derivative estimation and observer output estimation errors are bounded, the control algorithm proposed in this paper can enable the system to fully track the desired trajectory without the need for real-time updates of state information. Finally, the effectiveness of the proposed control algorithm is further verified by simulation cases.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6463-6474"},"PeriodicalIF":3.2,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101018","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":"Distributed Self-Triggered Formation Control for Multiple Mobile Robots With Dynamic Mappings","authors":"Yutong Liu,&nbsp;Peng Shi,&nbsp;Xiaojie Su,&nbsp;Hongjun Yu,&nbsp;Yue Yang","doi":"10.1002/rnc.70002","DOIUrl":"https://doi.org/10.1002/rnc.70002","url":null,"abstract":"<p>This article proposes a distributed self-triggered formation control scheme for a group of mobile robots to achieve a desired formation. The robots are assumed to have convex polygon geometric properties. Switching modes are introduced into the distributed formation controller design to balance formation moving and inter-robot collision avoidance of the whole group. A dual-channel self-triggered mechanism is proposed based on the control update triggering time and mapping communication trigger time, in which robots only send their states and mapping information at their event sequences. Establishing this mechanism can effectively equalize the amount of transmitted information and transmission consumption. The minimum control input update time and communication time are introduced to reinforce the robots' ability to run stably and improve the system's robustness. A dynamic mapping scheme is developed based on the desired formation and the time-varying collision conditions to reduce the impact of external environmental perturbations on robot operation while improving the efficiency and robustness of group formation. Simulations are given to demonstrate the effectiveness and performance of the novel distributed self-triggered formation control scheme.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6444-6462"},"PeriodicalIF":3.2,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Robust Event-Triggered Optimal Control for Lower Limb Exoskeleton Robots With Friction and Unknown Perturbations in an Interactive Environment","authors":"Linpu He,&nbsp;Jingxuan Cai,&nbsp;Rui Luo,&nbsp;Junfu Li,&nbsp;Zhinan Peng,&nbsp;Kaibo Shi","doi":"10.1002/rnc.70000","DOIUrl":"https://doi.org/10.1002/rnc.70000","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, we propose a new adaptive critic neural networks (Critic-NNs) learning algorithm for robust optimal tracking control of nonzero-equilibrium lower limb exoskeleton robots (LLER) with friction and unknown perturbations in an interactive environment. By introducing a nominal system, the robust tracking control of the original system is transformed into an optimal tracking control problem of the nominal system. The traditional adaptive dynamic programming (ADP) algorithm has strict restrictions on the system, which must satisfy the condition that the equilibrium point is zero and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>f</mi>\u0000 <mo>(</mo>\u0000 <mn>0</mn>\u0000 <mo>)</mo>\u0000 <mo>=</mo>\u0000 <mn>0</mn>\u0000 </mrow>\u0000 <annotation>$$ f(0)=0 $$</annotation>\u0000 </semantics></math>. However, in practice, these limits are difficult to achieve. To overcome this problem, we design a new cost function that successfully removes this limitation. At the same time, in order to improve the motion accuracy and control effect, the effects of joint friction torque and interaction forces between the LLER and the user on the system dynamics are considered. Aiming at the difficulty of solving the Hamilton–Jacobi–Bellman (HJB) equation, a critic neural network learning framework is designed to approximate the optimal cost function, and auxiliary terms are introduced to eliminate the requirement of initial stability control. Throughout the entire learning process, the update of the controller is driven by an event-triggered mechanism, which significantly reduces the computational burden on the robotic system. Finally, the effectiveness of the proposed algorithm is verified through simulation experiments.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6413-6428"},"PeriodicalIF":3.2,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101032","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":"Guaranteed Self-Triggered Control of Disturbed Systems: A Set Invariance Approach","authors":"Florian Pouthier,&nbsp;Sylvain Durand,&nbsp;Nicolas Marchand,&nbsp;Jonathan Dumon,&nbsp;Abdoullah Ndoye,&nbsp;Amaury Negre,&nbsp;Pierre Susbielle,&nbsp;Jose J. Castillo-Zamora,&nbsp;J. Fermi Guerrero Castellanos,&nbsp;Franck Ruffier","doi":"10.1002/rnc.8060","DOIUrl":"https://doi.org/10.1002/rnc.8060","url":null,"abstract":"<div>\u0000 \u0000 <p>This article introduces a novel self-triggering strategy designed to ensure the control of discrete-time linear systems with guaranteed stability, even in the presence of disturbances and uncertainties. This strategy aims to consistently maintain satisfaction of state constraints while accounting for the uncertainties in the system through a set-membership description. The self-triggering framework primarily relies on reachable and invariant sets. Reachable sets quantify the maximum deviation of the disturbed system from the predicted behavior, while an invariant set establishes triggering bounds for these reachable sets. This control method is intended to minimize the number of measurements required, thereby avoiding network bandwidth saturation. To validate the effectiveness of the proposed strategy, the experiments are conducted on an air extractor system, demonstrating a reduction in the number of measurement samples while ensuring stability and satisfying system state constraints.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6429-6443"},"PeriodicalIF":3.2,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101033","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":"Global Stability of Unmanned Surface Vehicles With Optimal Thrust Allocation Using Lyapunov-Based Model Predictive Fault-Tolerant Control","authors":"Yuxing Zhou,&nbsp;Li-Ying Hao,&nbsp;Run-Zhi Wang","doi":"10.1002/rnc.8066","DOIUrl":"https://doi.org/10.1002/rnc.8066","url":null,"abstract":"<div>\u0000 \u0000 <p>Conventional fault-tolerant control schemes, which compensate control signals based on actuator fault information, fail to reallocate control efforts to healthier ones, resulting in control inefficiency and exacerbated actuator damage. To deal with this problem, the article proposes a Lyapunov-based model predictive control (LMPC) optimization scheme that incorporates thrust allocation of unmanned surface vehicles (USVs) subject to disturbances, actuator faults, and saturations. Firstly, an auxiliary control system, incorporating the faults and disturbance observer and a sliding mode control law with an anti-windup compensator, is integrated into the LMPC framework. This integration ensures global stability and guarantees the feasibility of the optimization problem for any initial conditions, even with disturbances and actuator faults. Secondly, a fault-informed thrust allocation strategy is incorporated into the LMPC optimization framework. Upon actuator failure, the control weight is dynamically adjusted based on fault information, after which the LMPC optimization capabilities are employed to fine-tune the allocation of control signals. This approach not only optimizes thrust allocation but also reduces resource consumption while safeguarding the faulty actuator. Finally, simulation results demonstrate the efficacy and superiority of the proposed algorithm.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6399-6412"},"PeriodicalIF":3.2,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101009","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":"Diffusion-Induced Barrier Coverage of Multi-Layer Robotic Sensing Networks With Adaptive Scheduling Strategy","authors":"Pengyang Fan,&nbsp;Chao Zhai,&nbsp;Hehong Zhang","doi":"10.1002/rnc.8058","DOIUrl":"https://doi.org/10.1002/rnc.8058","url":null,"abstract":"<div>\u0000 \u0000 <p>The timely identification of external intruders is crucial to the protection of concerned regions or targets against malicious attacks. Multi-agent barrier coverage provides a powerful framework for the effective deployment of sensor networks to monitor baleful intruders. This paper aims to address the barrier coverage problem of robotic sensing networks by developing a multi-layer coverage formulation. Inspired by gas diffusion, a group of robotic sensors are scattered to expand the coverage territory from a gathering spot. With the assistance of a divide-and-conquer scheme, a distributed control algorithm is proposed to partition the defence barrier into multiple curve segments and integrate it with intruder monitoring. By adaptively scheduling robotic sensors among multi-layer networks, it contributes to maximizing the joint detection probability of sensing networks against external intruders. Moreover, theoretical analysis is conducted to acquire sufficient conditions for elevating the detection quality of a multi-layer sensing network. Finally, numerical simulations and robotic experiments are carried out to demonstrate the effectiveness of the proposed barrier coverage approach.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6368-6381"},"PeriodicalIF":3.2,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101008","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":"Dynamic Event-Triggered Adaptive Observer-Based Time-Varying Formation-Containment Tracking of Multiagent Systems With Input Saturation","authors":"Xinyu Zhang,&nbsp;Xisheng Zhan,&nbsp;Jie Wu,&nbsp;Tao Han,&nbsp;Lingli Cheng","doi":"10.1002/rnc.8061","DOIUrl":"https://doi.org/10.1002/rnc.8061","url":null,"abstract":"<div>\u0000 \u0000 <p>We investigate the time-varying formation-containment (TVFC) tracking problem for linear multiagent systems (MASs) with input saturation in this article. First, dynamic event-triggered (DET) strategies are put forward to regulate the interagent communication. Because there is no need for continuous interaction between agents, this strategy greatly reduces communication costs. Then, under the designed adaptive output feedback (OF) TVFC tracking control algorithm, it is demonstrated using Lyapunov stability theory that this system can realize the desired TVFC tracking. Moreover, we propose continuous protocols to avoid large chattering resulting from non-zero inputs. The errors are uniformly ultimately bounded and converges to an arbitrarily small zero neighborhood under the protocols. Moreover, no agent exhibits Zeno behavior for the constructed DET scheme. Finally, we demonstrate the feasibility of the designed DET control mechanism through simulation examples.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6382-6398"},"PeriodicalIF":3.2,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101010","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":"Zero-Order-Hold Based Event-Triggered Control for a Class of Approximately Feedback Linearized Systems","authors":"Sang-Young Oh,&nbsp;Ho-Lim Choi","doi":"10.1002/rnc.7999","DOIUrl":"https://doi.org/10.1002/rnc.7999","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, a new event-triggered controller is proposed that combines a zero-order-hold mechanism for the global asymptotic stabilization of a class of approximately feedback linearized systems. Together with a new event-triggering condition coupled with a zero-order-hold mechanism, a novel approach to the system analysis is developed that differs from the traditional event-triggered control approach. Based on the new system analysis, a control parameter selection guide is then provided for the state convergence speed and the number of control input updates. Several comparative examples illustrate the improved features of the proposed control method over the traditional event-triggered control method.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 13","pages":"5730-5746"},"PeriodicalIF":3.2,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144910462","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":"On Convergence of Fractional-Order Tracking Differentiators","authors":"Zu-Feng Zhang,&nbsp;Shou-Bo Jin,&nbsp;Zhi-Liang Zhao,&nbsp;Ze-Hao Wu","doi":"10.1002/rnc.8067","DOIUrl":"https://doi.org/10.1002/rnc.8067","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the convergence of nonlinear fractional-order tracking differentiators employing Caputo derivatives. Despite their significance, the convergence of fractional-order tracking differentiators has not been rigorously established to date. This paper addresses the gap in existing convergence proofs and offers a rigorous demonstration of the fractional-order tracking differentiators utilizing Caputo derivatives. Examples and numerical simulations are conducted to validate the effectiveness of the proposed results.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"35 15","pages":"6359-6367"},"PeriodicalIF":3.2,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145102216","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}