International Journal of Robust and Nonlinear Control最新文献

A Dual Progressive Extended Kalman Filter for Nonlinear Systems With Unknown Noises 含未知噪声非线性系统的双递进扩展卡尔曼滤波器

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-19 DOI: 10.1002/rnc.70677

Xiduan Chen, Ping Lin, Yuezhong Qian, Li Zhu

{"title":"A Dual Progressive Extended Kalman Filter for Nonlinear Systems With Unknown Noises","authors":"Xiduan Chen, Ping Lin, Yuezhong Qian, Li Zhu","doi":"10.1002/rnc.70677","DOIUrl":"https://doi.org/10.1002/rnc.70677","url":null,"abstract":"<div>\u0000 \u0000 <p>Kalman filtering works well in theory, but in practice, unknown noise from complex environments often degrades its performance—sometimes causing outright divergence. A Dual Progressive Extended Kalman filter (DPEKF) method is proposed for nonlinear systems with unknown noise. The existence of unknown noise will amplify the linearization error in nonlinear filtering, especially when the outliers in the equivalent test significantly reduce the overlap between the prior probability density distribution and the likelihood distribution. In order to solve this problem, the pseudo-time variable is introduced into the prior probability density and likelihood function at the same time, and the update equation of the Dual Progressive Extended Kalman filter (DPEKF) is derived. The robustness and estimation accuracy of the filter are effectively improved by extending the overlap region of prior distribution and the likelihood distribution and adopting a reasonable path function strategy. Furthermore, the introduction of convergence termination conditions effectively improves the computational efficiency and adaptive ability of the algorithm. Theoretical analysis shows that this method can maintain the boundedness of the state estimation error in the filtering process. Finally, simulation results based on a nonlinear target tracking example show that, compared with traditional methods such as EKF, IEKF, PEKF, HMKF, and MCCKF, DPEKF achieves superior robustness and estimation accuracy.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7639-7651"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177131","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

Sampled-Data PID Control Design for a Class of Uncertain Planar Nonlinear Systems 一类不确定平面非线性系统的采样数据PID控制设计

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-19 DOI: 10.1002/rnc.70672

Chih-Chiang Chen, Shin-Yu Wu, Hsiang-Yu Hsieh

{"title":"Sampled-Data PID Control Design for a Class of Uncertain Planar Nonlinear Systems","authors":"Chih-Chiang Chen, Shin-Yu Wu, Hsiang-Yu Hsieh","doi":"10.1002/rnc.70672","DOIUrl":"https://doi.org/10.1002/rnc.70672","url":null,"abstract":"<div>\u0000 \u0000 <p>This work addresses the synthesis of a sampled-data proportional—integral—derivative (PID) controller for the regulation problem of a class of uncertain planar nonlinear systems in the presence of parametric uncertainties and unknown exogenous constant disturbances. The foundational and underlying philosophy behind the proposed methodology is primarily grounded in an ingenious and judicious leveraging of the <i>feedback domination</i> principle, which elegantly establishes a subtle framework endowed with a tunable <i>domination gain</i> and thereby technically constitutes a transparent and intuitive approach for specifying the control gains and quantifying the <i>maximum allowable sampling period</i>, leading to the construction of a valid sampled-data PID controller that productively compensates for uncertain nonlinearities, parametric uncertainties, and unknown exogenous constant disturbances while competently and rigorously guaranteeing the attainment of the regulation objective. The notable novelty of this work mainly owes to an explicit design strategy addressing the challenging issue of constructing a viable sampled-data PID controller for uncertain planar nonlinear systems, together with a concrete guideline directing the systematic joint selection of validated sampled-data PID control gains and an admissible sampling period toward the regulation purpose. An illustrative numerical example is provided to demonstrate the applicability and efficacy of the presented scheme.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7627-7638"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177135","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 Stabilization of Mechanical Systems With Underactuation Degree One and Uncertainties Based on Controlled Lagrangians 欠驱动1度不确定机械系统的控制拉格朗日自适应镇定

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-21 DOI: 10.1002/rnc.70660

Guanjun Chen

{"title":"Adaptive Stabilization of Mechanical Systems With Underactuation Degree One and Uncertainties Based on Controlled Lagrangians","authors":"Guanjun Chen","doi":"10.1002/rnc.70660","DOIUrl":"https://doi.org/10.1002/rnc.70660","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper addresses the stabilization control problem for mechanical systems with underactuation degree one and inertia parameter uncertainties, based on the controlled Lagrangian (CL) method. A novel adaptive control strategy is first proposed by integrating the CL method with adaptive control theory, which effectively extends the applicability of the CL framework to systems with parameter uncertainties. The adaptive control strategy consists of three steps. First, a desired-though not directly implementable-controller that ensures closed-loop stability is derived using the CL method. Then, an implementable nominal controller is constructed, along with an adaptive compensator to correct the error between the nominal and desired control laws. Finally, an adaptive parameter update law is designed to guarantee the stability of the overall closed-loop system. As a case study, the proposed method is applied to stabilize a two degree of freedom Pendubot with inertia parameter uncertainties around its equilibrium point. Numerical simulations confirm the effectiveness and correctness of the designed controller.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7678-7693"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177525","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

Feedback Linearisation with State Constraints 状态约束的反馈线性化

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-15 DOI: 10.1002/rnc.70670

Songlin Jin, Yuanbo Nie, Morgan Jones

{"title":"Feedback Linearisation with State Constraints","authors":"Songlin Jin, Yuanbo Nie, Morgan Jones","doi":"10.1002/rnc.70670","DOIUrl":"https://doi.org/10.1002/rnc.70670","url":null,"abstract":"<p>Feedback Linearisation (FBL) is a widely used technique that applies feedback laws to transform input-affine nonlinear control systems into linear control systems, allowing for the use of linear controller design methods such as pole placement. However, for problems with state constraints, controlling the linear system induced by FBL can be more challenging than controlling the original system. This is because simple state constraints in the original nonlinear system become complex nonlinear constraints in the FBL induced linearised system, thereby diminishing the advantages of linearisation. To avoid increasing the complexity of state constraints under FBL, this paper introduces a method to first augment system dynamics to capture state constraints before applying FBL. We show that our proposed augmentation method leads to ill-defined relative degrees at state constraint boundaries. However, we show that ill-defined relative degrees can be overcome by using a switching FBL controller. Numerical experiments illustrate the capabilities of this method for handling state constraints within the FBL framework.</p>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7579-7595"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/rnc.70670","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177536","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}

引用次数: 0

Asymmetric Lyapunov–Krasovskii Functional Method for Reachable Set Estimation and Controller Design of Singular Nonlinear Systems With Time-Varying Delays 时变时滞奇异非线性系统可达集估计的非对称Lyapunov-Krasovskii泛函方法及控制器设计

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-26 DOI: 10.1002/rnc.70681

Le Huy Vu

引用次数: 0

Observer-Based Stipulated-Time Formation Tracking of Switching Multi-Agent Systems With Adjustable Transient Behavior 具有可调瞬态行为的切换多智能体系统基于观测器的规定时间编队跟踪

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-15 DOI: 10.1002/rnc.70661

Zhimin Xu, Hao An, Changhong Wang

{"title":"Observer-Based Stipulated-Time Formation Tracking of Switching Multi-Agent Systems With Adjustable Transient Behavior","authors":"Zhimin Xu, Hao An, Changhong Wang","doi":"10.1002/rnc.70661","DOIUrl":"https://doi.org/10.1002/rnc.70661","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the distributed stipulated-time formation tracking problem for second-order multi-agent systems (MASs) under both fixed and switching communication topologies. In contrast to existing predefined-time and prescribed-time approaches that only guarantee convergence within a conservative upper bound, the proposed method enables the exact settling time of both estimation and tracking errors to be explicitly assigned, independent of initial conditions. Improved stipulated-time distributed observers are developed for both scenarios, where a single design parameter can directly preassign the actual convergence time. Based on the observer design, an observer-based formation control framework is constructed to ensure that all agents achieve the desired formation precisely at the specified time. Furthermore, a class of time-varying regulation functions is incorporated into the control design to explicitly shape the transient behavior while avoiding excessively large control gains, thereby enhancing practical applicability. Theoretical analysis, along with numerical simulations and physical experiments, validates the effectiveness and robustness of the proposed approach. Overall, the proposed framework provides improved temporal accuracy, enhanced transient flexibility, and better practical performance compared with existing prescribed-time methods.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7550-7566"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177534","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 Secure Consensus Control of Switched Filter-Based High-Order Fully Actuated MASs Under DoS Attacks DoS攻击下基于交换滤波器的高阶全致动质量自适应模糊安全一致性控制

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-26 DOI: 10.1002/rnc.70680

Rongmei Li, Xin Huo, Weizhen Liu, Kemao Ma, Ruihang Ji

{"title":"Adaptive Fuzzy Secure Consensus Control of Switched Filter-Based High-Order Fully Actuated MASs Under DoS Attacks","authors":"Rongmei Li, Xin Huo, Weizhen Liu, Kemao Ma, Ruihang Ji","doi":"10.1002/rnc.70680","DOIUrl":"https://doi.org/10.1002/rnc.70680","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper addresses the adaptive secure consensus control of high-order fully actuated multi-agent systems (MASs) under denial-of-service (DoS) attacks. To deal with the transmitted data from the leader and neighbors which are unavailable in the presence of DoS attacks, an observer-based switched filter is proposed to estimate the output of the system and its high-order derivatives, which switches between intervals with and without attacks, making zero estimation errors possible. This active switching mechanism ensures zero estimation errors and effectively accommodates the attack impacts. Then, a high-gain observer based on a differentiator is designed to avoid the differential explosion problem and the adaptive parameters are designed to fit the weights of fuzzy logic systems (FLSs) to approximate the unknown nonlinearity when the high-order backstepping technique is applied. Unlike classical state-space methods, which require transforming the model into a first-order system and only consider first-order state consensus, a controller based on the fully actuated characteristic is subsequently proposed to ensure high-order state consensus of the MASs. It is strictly demonstrated that all closed-loop variables achieve global uniform ultimate boundedness, with the consensus tracking errors asymptotically converging to zero under DoS attacks. Ultimately, the effectiveness of the proposed control method is illustrated through a numerical simulation.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7727-7744"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177705","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

Fixed-Time Formation Tracking of Multiple USVs With DoS Attacks: A Reinforcement Learning Control Method 具有DoS攻击的多usv的固定时间编队跟踪：一种强化学习控制方法

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-22 DOI: 10.1002/rnc.70674

Ze-Jiang Chang, Xiang-Yu Yao, Ju H. Park

引用次数: 0

Finite-Time Observer-Based Adaptive Iterative Learning Control for Output Tracking of Uncertain High-Order Fully Actuated Systems 不确定高阶全驱动系统输出跟踪的有限时间观测器自适应迭代学习控制

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-19 DOI: 10.1002/rnc.70682

Junkai Wang, Xiao-Dong Li, Xuefang Li

{"title":"Finite-Time Observer-Based Adaptive Iterative Learning Control for Output Tracking of Uncertain High-Order Fully Actuated Systems","authors":"Junkai Wang, Xiao-Dong Li, Xuefang Li","doi":"10.1002/rnc.70682","DOIUrl":"https://doi.org/10.1002/rnc.70682","url":null,"abstract":"<div>\u0000 \u0000 <p>Most existing adaptive iterative learning control (AILC) schemes, while effective for state tracking for repetitive systems, rely on full state measurement. Although observer-based AILC methods can achieve output tracking, they are predominantly hampered by observers with asymptotic convergence, which conflict with the finite-time operation of AILC. To overcome the limitations, this article proposes a novel finite-time observer-based AILC scheme for a class of nonlinear high-order fully actuated (HOFA) systems with input disturbances. By leveraging the HOFA system framework, the proposed approach first converts the original nonlinear HOFA system into a linear closed-loop system, which facilitates the construction of a linear finite-time observer and furthermore develops a corresponding AILC law. Rigorous convergence analysis of the constructed observer and the proposed AILC algorithm is conducted. The effectiveness of the proposed AILC method is validated through two illustrative examples and comparative studies with existing algorithms.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7665-7677"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177133","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 Leader-Following Bipartite Consensus of High-Order Nonlinear Multi-Agent Systems With Unknown Control Coefficients and Mismatched Uncertainties 具有未知控制系数和不匹配不确定性的高阶非线性多智能体系统的自适应领导-跟随二部共识

IF 3.1 3区计算机科学

International Journal of Robust and Nonlinear Control Pub Date : 2026-10-12 Epub Date: 2026-07-15 DOI: 10.1002/rnc.70669

Tiantian Guo, Pengjuan Yang, Na Huang, Shuping Wang, Hong-Xiang Hu

{"title":"Adaptive Leader-Following Bipartite Consensus of High-Order Nonlinear Multi-Agent Systems With Unknown Control Coefficients and Mismatched Uncertainties","authors":"Tiantian Guo, Pengjuan Yang, Na Huang, Shuping Wang, Hong-Xiang Hu","doi":"10.1002/rnc.70669","DOIUrl":"https://doi.org/10.1002/rnc.70669","url":null,"abstract":"<div>\u0000 \u0000 <p>Multi-agent systems (MASs) in cooperative-competitive networks have wide applications, ranging from social networks to robotic swarms. However, their control design becomes more complicated for systems with high-order dynamics and multiple uncertainties, due to the inherent strong coupling. This article addresses the adaptive leader-following bipartite consensus for a class of high-order uncertain nonlinear systems. Specifically, the leader and followers share the system nonlinearities and matched uncertainties, while the latter additionally allow the unknown control coefficients and mismatched uncertainties. For this, a backstepping-based adaptive control strategy is developed. Several adaptive gains, one of which directly estimates the unknown control coefficients in the first <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>n</mi>\u0000 <mo>−</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <annotation>$$ n-1 $$</annotation>\u0000 </semantics></math> steps, are designed, thereby ensuring the achievement of asymptotic bipartite consensus. A simulation example validates the effectiveness of the proposed scheme.</p>\u0000 </div>","PeriodicalId":50291,"journal":{"name":"International Journal of Robust and Nonlinear Control","volume":"36 17","pages":"7567-7578"},"PeriodicalIF":3.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149177535","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