International Journal of Adaptive Control and Signal Processing最新文献

{"title":"Hierarchical Iterative Parameter Estimation for Multivariable Systems Based on the Coupled Identification Model","authors":"Feng Ding,&nbsp;Hao Fang,&nbsp;Chun Wei,&nbsp;Ling Xu","doi":"10.1002/acs.70110","DOIUrl":"https://doi.org/10.1002/acs.70110","url":null,"abstract":"<div>\u0000 \u0000 <p>The partially-coupled information vector system refers to a multivariable system in which some of the information (inputs) among sub-systems are coupled, while the rest of the information (outputs) are uncoupled (independent). After parameterizing such a multivariable system, we obtain a partially-coupled information vector identification model. Based on this coupled identification model, we propose corresponding iterative parameter identification methods, including hierarchical gradient-based iterative algorithms, hierarchical least-squares-based iterative algorithms, hierarchical multi-innovation gradient-based iterative algorithms, and hierarchical multi-innovation least-squares-based iterative algorithms, etc. These iterative parameter identification methods can be extended to other linear and nonlinear multivariate stochastic systems with colored noise.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 10","pages":"2009-2034"},"PeriodicalIF":3.8,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149125759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Control for Flexible Exoskeleton Robots Subject to Full-State Constraints and No Feasibility Condition","authors":"Aiqing Chen,&nbsp;Xiang Liu,&nbsp;Weiguo Zhang,&nbsp;Hao Zhou","doi":"10.1002/acs.70105","DOIUrl":"https://doi.org/10.1002/acs.70105","url":null,"abstract":"<div>\u0000 \u0000 <p>For the <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>n</mi>\u0000 </mrow>\u0000 <annotation>$$ n $$</annotation>\u0000 </semantics></math>-link upper limb flexible exoskeleton robots, an adaptive constraint control strategy is introduced in this work, which does away with reliance on the feasibility requirements of virtual controllers and input saturation. Firstly, a nonlinear transformation that relies solely on the constrained variables is constructed to directly handle the full-state constraints with asymmetric property during the operation of exoskeleton robots, ensuring that all states are within a reasonable range. Secondly, considering the complexity of the exoskeleton robot system and the requirement for high-precision control, a new coordinate transformation is put forward and incorporated into the framework of backstepping algorithm which is based on dynamic surface control, effectively avoiding the stringent feasibility condition limitations of the virtual controller and optimizing the control process. The above method eliminates the cumbersome offline feasibility verification calculations, granting designers greater freedom in parameter selection. Ultimately, the validity of the suggested method is confirmed via simulation study.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1836-1847"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Mixed \u0000 \u0000 \u0000 \u0000 \u0000 H\u0000 \u0000 \u0000 2\u0000 \u0000 \u0000 /\u0000 H\u0000 ∞\u0000 \u0000 $$ {H}_2/Hinfty $$\u0000 Output Trace Control for Complex Water Network","authors":"Mengqiu Shen,&nbsp;Hua Chen,&nbsp;Shaoyan Liu,&nbsp;Shengjie Yang","doi":"10.1002/acs.70100","DOIUrl":"https://doi.org/10.1002/acs.70100","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper addresses output-tracking control for complex urban water distribution networks with multiple time-varying delays and develops a feedback synthesis framework based on linear matrix inequalities (LMI). Guided by the network's interconnection structure, the physical system is abstracted as a discrete-time multi-delay model. An augmented Lyapunov–Krasovskii functional with free-weighting matrices is constructed to derive LMI sufficient conditions that guarantee asymptotic stability and provide upper bounds on the mixed <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mi>H</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mn>2</mn>\u0000 </mrow>\u0000 </msub>\u0000 <mo>/</mo>\u0000 <msub>\u0000 <mrow>\u0000 <mi>H</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mi>∞</mi>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {H}_2/{H}_{infty } $$</annotation>\u0000 </semantics></math> tracking performance. These conditions in turn enable a convex controller-synthesis procedure. Numerical simulations demonstrate fast, robust, and energy-efficient reference tracking in the presence of multiple delays and exogenous disturbances. The results furnish a computable, implementation-ready design tool for pressure regulation and operational scheduling in urban water-supply systems, with strong prospects for engineering deployment.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1780-1793"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Steering Feel Control for Steer-By-Wire Vehicles Under Uncertainties and Time Delay","authors":"Guan Zhou,&nbsp;Zhongbao Li,&nbsp;Yutao Jin,&nbsp;Haojie Deng,&nbsp;Demin Hu","doi":"10.1002/acs.70108","DOIUrl":"https://doi.org/10.1002/acs.70108","url":null,"abstract":"<div>\u0000 \u0000 <p>In steer-by-wire (SBW) vehicles, the steering feel feedback system is essential for providing realistic torque feedback to the driver. However, its performance is often degraded by the simultaneous presence of system uncertainties and time-varying delays caused by communication and computation. While existing studies have addressed either uncertainty or delay separately, their combined effect remains underexplored. This article proposes a novel integrated control framework that simultaneously handles both challenges. First, a barrier function-based adaptive super-twisting sliding mode control (STSMC) is employed to ensure robustness against system uncertainties. To further mitigate communication-induced delays, a relative threshold event-triggered mechanism is introduced, which significantly reduces unnecessary data transmission compared with conventional fixed-threshold methods. Second, to compensate for residual time-varying delays that cannot be eliminated by event-triggering alone, a Grey-Markov time delay prediction model is developed. This model combines grey system theory for trend extraction and Markov chains for stochastic fluctuation correction, enabling accurate real-time delay estimation. The predicted delay is then integrated into a fuzzy adaptive Smith predictor, which dynamically adjusts compensation parameters to enhance system robustness and response speed. Simulation results under high-speed and low-speed steering conditions demonstrate that the proposed strategy reduces the maximum absolute error by more than 50% and the root mean square error by more than 10% compared with conventional Markov-based methods, while also reducing communication frequency.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1885-1902"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Consensus-Based Formation Control of Nonholonomic Vehicles With Disturbances and Input Constraints","authors":"Angel I. Paredes,&nbsp;Jose Guadalupe Romero,&nbsp;Emmanuel Nuño","doi":"10.1002/acs.70098","DOIUrl":"https://doi.org/10.1002/acs.70098","url":null,"abstract":"<div>\u0000 \u0000 <p>This work presents a novel decentralized formation controller for networks of perturbed nonholonomic vehicles. The proposed controller is robust against unknown constant disturbances and mitigates actuator stress by addressing input saturation with a smooth control approach. A mathematical proof of convergence is provided, supported by numerical simulations that compare the performance of the proposed controller to an unbounded and a non robust control schemes.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1771-1779"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Neural Network Output Feedback Optimal Saturation Control for Single-Phase Photovoltaic Grid-Connected Power Systems","authors":"Hongyang Zhang,&nbsp;Tiechao Wang,&nbsp;Tingfeng Zhang","doi":"10.1002/acs.70107","DOIUrl":"https://doi.org/10.1002/acs.70107","url":null,"abstract":"<div>\u0000 \u0000 <p>The adaptive neural network (NN) output feedback optimal saturation control scheme is investigated for a single-phase photovoltaic (PV) grid-connected power system with partially unavailable states. The unavailable states are estimated by a state observer. The output feedback control scheme combines the adaptive dynamic programming (ADP) approach with the dynamic surface control (DSC) technique based on the backstepping design framework, in which the DSC technique can simplify the computation. By constructing an observer-critic-actor architecture, NNs are utilized via reinforcement learning (RL) to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation, such that the difficulty of solving the HJB equation is overcome. By integrating the hyperbolic tangent function with a first-order auxiliary system, the adverse influence of the saturated links is removed. All the variables of the closed-loop PV power system are proved to be semi-globally uniformly ultimately bounded (SGUUB) by the Lyapunov stability theory. The simulation and comparative results show the feasibility and superiority of the presented control scheme.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1866-1884"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Fuzzy Control Strategy for Full-State-Constrained Nonlinear Systems: A Command-Filtered Fault-Tolerant Technology","authors":"Shanyuan Xu,&nbsp;Tingting Zhu,&nbsp;Zong-yao Sun,&nbsp;Junsheng Zhao","doi":"10.1002/acs.70111","DOIUrl":"https://doi.org/10.1002/acs.70111","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes an adaptive fuzzy fault-tolerant tracking strategy for uncertain nonlinear systems subject to full-state constraints and potential faults in sensors and actuators. To address the problems caused by full-state constraints, a barrier function is employed as an analytical tool to ensure that the system's state remains within a safe operational range. Meanwhile, the combined use of parameter separation and multi-adaptive law techniques effectively minimizes the influence of faults on system performance. Additionally, a finite-time command filter with error-compensation signals is embedded to prevent explosion of complexity. To further alleviate the communication load, an event-triggered fault-tolerant controller is designed, effectively avoiding Zeno behavior. The design of this controller ensures that all signals in the system remain bounded and enables the output signal to track the reference signal within a predetermined error range. In the end, the validity of the proposed strategy is confirmed by simulation results.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1903-1916"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Output-Feedback Adaptive Boundary Control of Scalar Hyperbolic ODE–PDE–ODE Cascade Systems","authors":"Runsheng Guo,&nbsp;Min Ma,&nbsp;Jianbin Qiu,&nbsp;Wenqiang Ji,&nbsp;Kangkang Sun","doi":"10.1002/acs.70101","DOIUrl":"https://doi.org/10.1002/acs.70101","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents an output feedback adaptive boundary control scheme for a hyperbolic ODE–PDE–ODE cascade system with significant uncertainties. The system considers that all parameters, including spatially varying ones, are unknown and that only the ODE subsystem states are measurable. To facilitate the control design, an equivalent system representation is first derived. State observers are then constructed using linear combinations of ODE–PDE cascade filters, while swapping identifiers provide online parameter estimates. By integrating these elements, an adaptive backstepping control law is designed. It is proved that the proposed adaptive control law can stabilize the studied system. Finally, the effectiveness of the derived controller is verified via numerical simulations.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1807-1817"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148872092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Command-Filtered Prescribed Performance Control of Quadrotor UAVs With External Disturbances","authors":"Mingchao Liu,&nbsp;Ming Chen,&nbsp;Xiaoxuan Jiao,&nbsp;Yulin Gai","doi":"10.1002/acs.70112","DOIUrl":"https://doi.org/10.1002/acs.70112","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes an adaptive fixed-time prescribed performance trajectory tracking control strategy based on finite-time command filtering for a class of quadrotor systems affected by external disturbances. Firstly, a nonlinear mapping and an error transformation function are introduced to establish an equivalent error model. Secondly, based on the backstepping method, fixed-time control, and adaptive control, a command-filter-based prescribed performance trajectory tracking controller for quadrotor systems with external disturbances is designed. This control strategy incorporates a command filter and fuzzy logic systems into the control framework. The command filter effectively avoids the repeated differentiation problem of the virtual control laws, significantly reducing computational complexity. The fuzzy logic systems are used to approximate the disturbance terms and unknown nonlinear terms in the model, enhancing the systems' robustness. In addition, the combination of prescribed performance control and fixed-time control ensures that the system tracking error converges within the boundaries defined by the prescribed performance function within a fixed-time, and the convergence time is independent of the systems' initial conditions. Finally, simulations verify the effectiveness and superiority of the proposed control method.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1917-1931"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 New Takagi-Sugeno Fuzzy Control Method for Cohen-Grossberg Neural Networks With State-Dependent Impulses","authors":"Dona Ariani,&nbsp;Aili Fan,&nbsp;Yuchen Miao,&nbsp;Lin Du","doi":"10.1002/acs.70099","DOIUrl":"https://doi.org/10.1002/acs.70099","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the asymptotic stability of Cohen-Grossberg neural networks (CGNNs) formulated within the Takagi–Sugeno (T–S) fuzzy framework, with a focus on state-dependent impulsive effects. Impulses occurring at nonfixed instants present significant analytical challenges due to their unpredictable nature, which complicates stability analysis. To address this, the B-equivalence method is applied to transform the system into one with fixed-time impulses by determining the B-equivalent impulsive operator. This transformation simplifies the stability analysis and enables the application of Lyapunov functional techniques, along with comparison principles, to derive sufficient conditions for the asymptotic stability of the T–S fuzzy CGNNs. The proposed impulsive fuzzy control scheme ensures system stability by integrating fuzzy logic to model nonlinearities and applying impulsive control at strategically selected intervals. Two numerical examples are provided to validate the theoretical results, demonstrating the practical applicability of the approach in stabilizing complex neural networks subject to state-dependent impulsive actions and highlighting its potential for real-world systems requiring adaptive, nonlinear control.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 9","pages":"1758-1770"},"PeriodicalIF":3.8,"publicationDate":"2026-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148871971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}