International Journal of Robust and Nonlinear Control最新文献

{"title":"Affine Formation Control for End-Effectors of Networked Manipulators With Maneuvering Leaders and Unknown System Parameters","authors":"Yichao Ao,&nbsp;Qifeng Zhang,&nbsp;Yingmin Jia,&nbsp;Yang Liu","doi":"10.1002/rnc.70379","DOIUrl":"https://doi.org/10.1002/rnc.70379","url":null,"abstract":"<div>\u0000 \u0000 <p>This article studies the distributed control problem of collectively achieving and maneuvering the formation shape for the end-effectors of networked multiple Euler-Lagrange manipulators. In the formation process, precious few manipulators, called leaders, determine their motions autonomously, whereas a bulk of followers steer themselves to form the target geometric pattern and achieve desired affine transformation. For both undirected and directed graphs, distributed control protocols are proposed to achieve formation in the task space, but through the control inputs injected at joints' level, without using the absolute positions of the end-effectors. Meanwhile, distributed observers and adaptive laws are designed for each follower to estimate its desired behavior and both dynamic and kinematic unknown parameters. Moreover, a new kinematic adaptive law is proposed for undirected graph without using absolute velocity information. The asymptotic convergence of the closed-loop systems is proven, and the effectiveness of the proposed approach is validated by exemplary simulation examples of networked two-link manipulators.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3838-3854"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668734","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":"Observer-Based Control for T-S Fuzzy Singular Systems With Time Delay","authors":"Yilun Fang,&nbsp;Chong Lin","doi":"10.1002/rnc.70391","DOIUrl":"https://doi.org/10.1002/rnc.70391","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we delve into the observer-based control for Takagi-Sugeno (T-S) fuzzy singular systems with time delay, employing the asymmetric Lyapunov–Krasovskii functional (LKF) method. Our major innovation is constructing a new LKF using a special structure matrix <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>P</mi>\u0000 </mrow>\u0000 <annotation>$$ P $$</annotation>\u0000 </semantics></math>, which markedly reduces conservativeness compared to recent literature methods. Meanwhile, to further reduce the conservativeness of the results, we combine the membership-function-dependent method. The admissible sufficient conditions for the closed-loop system and the calculation methods of observer gain and controller gain are given by using linear matrix inequalities. To verify the effectiveness of our approach in reducing conservatism, we present two numerical examples and one practical example.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3914-3922"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668770","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":"Affine Formation Obstacle Avoidance Control for Multi-Agent Systems Under an Improved Disturbance Observer","authors":"Wen Qin,&nbsp;Mouquan Shen,&nbsp;Hamid Reza Karimi,&nbsp;Zheng Hong Zhu","doi":"10.1002/rnc.70398","DOIUrl":"https://doi.org/10.1002/rnc.70398","url":null,"abstract":"<div>\u0000 \u0000 <p>The paper addresses affine formation obstacle avoidance control of multi-agent systems (MASs) with unknown external disturbances. An improved disturbance observer is developed to enhance the estimation accuracy. An affine transformation and an adaptive controller are exploited to dynamically adjust formation against unknown obstructed environments. Sufficient criteria are established to achieve obstacle avoidance with zero velocity, constant velocity, and time-varying velocity, respectively. Finally, two examples are simulated to deliver the effectiveness of the proposed control schemes.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3979-3988"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668809","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":"Adaptive Sliding Mode Control for Uncertain Tilting Quadrotors Using Randomized Feedforward Neural Networks","authors":"Jing-Jing Xiong,&nbsp;Xiang-Yu Wang","doi":"10.1002/rnc.70396","DOIUrl":"https://doi.org/10.1002/rnc.70396","url":null,"abstract":"<div>\u0000 \u0000 <p>This study explores a control strategy for a tilting quadrotor UAV (TQUAV) subject to model uncertainties and time-varying mass. A novel sliding mode control (SMC) framework incorporating randomized feedforward neural networks (RFNNs) is developed to address the following adaptive challenges. First, for the uncertainty compensation, the adaptive laws based on RFNNs are designed to estimate unknown model uncertainties, time-varying mass, and external disturbances. Second, for the time-varying parameter adaptation, the neural network-driven adaptive mechanisms are introduced for online adjustment of unknown or time-dependent parameters within sliding manifolds. Third, for the approximation error mitigation, the conventional adaptive control techniques are employed to compensate for inherent neural network approximation errors. In addition, the closed-loop system's stability is rigorously proven by Lyapunov stability theory, ensuring asymptotic convergence of both positional and attitude tracking errors. Comparative numerical simulations are given to validate the superior performance of the proposed adaptive control architecture over conventional methods.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"4042-4055"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668818","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":"Adaptive Sliding Mode Control for Uncertain Tilting Quadrotors Using Randomized Feedforward Neural Networks","authors":"Jing-Jing Xiong,&nbsp;Xiang-Yu Wang","doi":"10.1002/rnc.70396","DOIUrl":"https://doi.org/10.1002/rnc.70396","url":null,"abstract":"<div>\u0000 \u0000 <p>This study explores a control strategy for a tilting quadrotor UAV (TQUAV) subject to model uncertainties and time-varying mass. A novel sliding mode control (SMC) framework incorporating randomized feedforward neural networks (RFNNs) is developed to address the following adaptive challenges. First, for the uncertainty compensation, the adaptive laws based on RFNNs are designed to estimate unknown model uncertainties, time-varying mass, and external disturbances. Second, for the time-varying parameter adaptation, the neural network-driven adaptive mechanisms are introduced for online adjustment of unknown or time-dependent parameters within sliding manifolds. Third, for the approximation error mitigation, the conventional adaptive control techniques are employed to compensate for inherent neural network approximation errors. In addition, the closed-loop system's stability is rigorously proven by Lyapunov stability theory, ensuring asymptotic convergence of both positional and attitude tracking errors. Comparative numerical simulations are given to validate the superior performance of the proposed adaptive control architecture over conventional methods.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"4042-4055"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668819","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":"A Constructive Approach to Multi-Variable Extremum Seeking With Discrete-Time Delayed Noisy Measurements","authors":"Xuefei Yang,&nbsp;Bowen Zhao,&nbsp;Emilia Fridman","doi":"10.1002/rnc.70368","DOIUrl":"https://doi.org/10.1002/rnc.70368","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we present a constructive method for multivariable gradient-based ES of static quadratic maps with discrete-time delayed noisy measurements, and provide mean-square exponential ultimate boundedness (MSEUB) analysis under essentially relaxed assumption on the unknown Hessian than the previous constructive methods. By employing the time-delay approach to averaging, we introduce an equivalent, approximation-free representation of the gradient-based ES estimation error system, which is the neutral type time-delay system with stochastic perturbations. We further present the latter system as a perturbed averaged ordinary differential equation and employ the variation of constants formula for the quantitative MSEUB analysis. The explicit condition in terms of simple scalar inequality depending on the dither frequencies and measurement noise intensity is established to guarantee the MSEUB analysis of the ES control system. The bounds on the maximum dither frequencies, measurement noise intensity tolerance margin, and the mean-square ultimate bound of the estimation error are provided. In addition, a qualitative stability result is also presented. Examples from the literature illustrate the efficiency of the results.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3807-3818"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668413","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":"Vehicle Tracking With Obstacle Avoidance Under Uncertainty Using Gaussian Processes and Backoffs","authors":"Mengxu Xie,&nbsp;Tong Ma","doi":"10.1002/rnc.70392","DOIUrl":"https://doi.org/10.1002/rnc.70392","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper tackles vehicle tracking and obstacle avoidance by integrating path planning into a model- and data-driven predictive control framework using Gaussian processes (GP-MDPC) and backoffs. Autonomous driving is inherently uncertain and stochastic, making vehicle tracking with obstacle avoidance a stochastic constrained control problem best addressed by stochastic nonlinear model predictive control (SNMPC). The proposed GP-MDPC approach offers two key advantages over the current state-of-the-art SNMPC. Firstly, GPs learn unknown dynamics from measurements, the predictions and uncertainty quantification generated by GPs are subsequently propagated through the nominal vehicle model for updating state mean and covariance equations. Besides, sparse GPs replace full GPs to reduce computational demand and speed up online evaluation. Secondly, a backoff approximation method is explored to reformulate the chance constraints into tractable expressions by tuning backoffs offline from generated closed-loop Monte Carlo samples. This method resolves the tradeoff between robustness and the risk of constraint violation, as well as guarantees online recursive feasibility. Compared to Chebyshev's inequality method, the backoff approach alleviates the conservatism caused by chance constraint approximation and thus improves vehicle tracking performance. The geometric relationship between the vehicle and obstacles is converted into chance constraints, which, together with the evolution equations for the state mean and covariance, are combined to formulate a finite-horizon stochastic optimal control problem. Simulations demonstrate that the sparse GP-MDPC using backoffs is more preferred than the full GP-MDPC either using backoffs or Chebyshev's inequality by improving computational efficiency while maintaining satisfactory tracking performance as well as safety.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3866-3882"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668416","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":"A Constructive Approach to Multi-Variable Extremum Seeking With Discrete-Time Delayed Noisy Measurements","authors":"Xuefei Yang,&nbsp;Bowen Zhao,&nbsp;Emilia Fridman","doi":"10.1002/rnc.70368","DOIUrl":"https://doi.org/10.1002/rnc.70368","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we present a constructive method for multivariable gradient-based ES of static quadratic maps with discrete-time delayed noisy measurements, and provide mean-square exponential ultimate boundedness (MSEUB) analysis under essentially relaxed assumption on the unknown Hessian than the previous constructive methods. By employing the time-delay approach to averaging, we introduce an equivalent, approximation-free representation of the gradient-based ES estimation error system, which is the neutral type time-delay system with stochastic perturbations. We further present the latter system as a perturbed averaged ordinary differential equation and employ the variation of constants formula for the quantitative MSEUB analysis. The explicit condition in terms of simple scalar inequality depending on the dither frequencies and measurement noise intensity is established to guarantee the MSEUB analysis of the ES control system. The bounds on the maximum dither frequencies, measurement noise intensity tolerance margin, and the mean-square ultimate bound of the estimation error are provided. In addition, a qualitative stability result is also presented. Examples from the literature illustrate the efficiency of the results.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3807-3818"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668732","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":"Comparative Analysis of the Performances of a Nonlinear Observer and Nonlinear Kalman Filters in the Presence of Non-Gaussian Disturbances","authors":"Hamidreza Movahedi,&nbsp;Ali Zemouche,&nbsp;Rajesh Rajamani","doi":"10.1002/rnc.70386","DOIUrl":"https://doi.org/10.1002/rnc.70386","url":null,"abstract":"<p>This paper focuses on state estimation for a fairly general class of systems, involving nonlinear functions and disturbances in both the process dynamics and output equations. A nonlinear observer that satisfies a <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>H</mi>\u0000 <mo>∞</mo>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {boldsymbol{H}}_{boldsymbol{infty}} $$</annotation>\u0000 </semantics></math> disturbance attenuation constraint in addition to providing asymptotic stability in the absence of disturbances is developed using Lyapunov analysis. A weighted form of this observer is able to adjust the estimation performance for systems that have states with considerably different levels of magnitude. The observer is shown analytically to provide a guaranteed upper bound on the vector norm of the estimation error, and this upper bound is utilized to guarantee the stability of observers in disturbed systems that are designed to be stable over a finite domain. The performance of the nonlinear observer is compared with the performance of the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). Three different applications are utilized for the comparison, consisting of a magnetic position estimation problem, a state-of-charge battery application, and a vehicle tracking application. In the case of the disturbances being Gaussian noise, the UKF and the nonlinear observer provide approximately the same level of performance, and they both surpass the performance of the EKF. However, in the case of 2-norm-bounded non-Gaussian noise, such as spikes/pulses, the nonlinear observer is shown to significantly outperform both the UKF and the EKF. Extensive experimental results and comparisons using a range of covariance choices demonstrate the superiority of the nonlinear observer, confirming that it is not just an artifact of specific tests.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"3896-3913"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.70386","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668771","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":"Finite-Time Synchronization of PDT Switched Stochastic Neural Networks under Event-Triggered Mechanism","authors":"Bo Liu,&nbsp;Yong Chen,&nbsp;Longsuo Li","doi":"10.1002/rnc.70395","DOIUrl":"https://doi.org/10.1002/rnc.70395","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the finite-time synchronization problem of master-slave stochastic neural network systems with switching signals. First, to improve resource utilization, an event-triggered mechanism is introduced, taking into account the transmission delay in the communication process, and a master-slave synchronization error system is established. Second, to overcome the limitations of traditional switching signals, a more versatile persistent dwell-time switching rule is adopted. By constructing appropriate Lyapunov–Krasovskii functionals combined with free-weight matrix methodology, sufficient conditions for the finite-time <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mi>ℋ</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mi>∞</mi>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {mathscr{H}}_{infty } $$</annotation>\u0000 </semantics></math> synchronization of the master-slave system are derived. Based on these, the controller expression is obtained via the singular value decomposition lemma. Finally, the effectiveness of the proposed method is verified through simulation examples.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 7","pages":"4002-4013"},"PeriodicalIF":3.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147668812","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}