International Journal of Adaptive Control and Signal Processing最新文献_第2页

Formation Control Design and Optimization for Uncertain Underactuated Robots Team Using Cooperative Game Theory 基于合作博弈论的不确定欠驱动机器人群体控制设计与优化

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-12-07 DOI: 10.1002/acs.70019

Chunsheng He, Jian Zhao, Ke Shao

{"title":"Formation Control Design and Optimization for Uncertain Underactuated Robots Team Using Cooperative Game Theory","authors":"Chunsheng He, Jian Zhao, Ke Shao","doi":"10.1002/acs.70019","DOIUrl":"https://doi.org/10.1002/acs.70019","url":null,"abstract":"<div>\u0000 \u0000 <p>This manuscript introduces an innovative approach to address the formation control challenges for a specific category of underactuated robots (UARs). It transforms the formation control problem into a constraint-following problem with three basic constraints: (1) The configuration constraints (CCs), which are to induce behaviors for each UAR. (2) The formation constraints (FCs), which are used to maintain the team formation. (3) The trajectory constraints (TCs), which are imposed to make the team move with a predefined formation. The UAR team is assumed to suffer from time-varying while bounded uncertainty, and the uncertainty bound is unknown. Invoking an interval method, we build a dynamic model for the uncertain UAR team. Considering the three basic constraints in a unified form, we then employ an improved adaptive formation controller based on an extended Udwadia-control (UC) scheme for the uncertain UAR team. The controller can guarantee the UAR team deterministic convergence, which is verified by an explicit Lyapunov analysis. As there are three tunable control gains in the proposed controller, this paper adopts a cooperative game (CG) algorithm to obtain the optimal formation control. Regarding the tunable parameters as three players in a CG with their cost functions representing the tracking performance or the energy cost, the optimal formation control is realized by achieving an equilibrium among players. Simulations on a UAR team consisting of three inverted pendulum robots (IPRs) are performed to test the designed optimal formation controller.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 3","pages":"692-709"},"PeriodicalIF":3.8,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147563873","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}

引用次数: 0

Finite-Time Sliding Mode Control for IT2 Fuzzy Nonhomogeneous Markovian Switched Systems: An Asynchronous Observer-Based Approach IT2模糊非齐次马尔可夫切换系统的有限时间滑模控制：基于异步观测器的方法

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-11-25 DOI: 10.1002/acs.70005

Yao Wang

引用次数: 0

Adaptive Neural Fixed-Time Command Filtered Control for Stochastic Nonlinear Systems With Input Quantization 输入量化随机非线性系统的自适应神经定时命令滤波控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-11-30 DOI: 10.1002/acs.70009

Long Gu, Lidong Wang, Xiaoping Liu, Aosen Zhang

{"title":"Adaptive Neural Fixed-Time Command Filtered Control for Stochastic Nonlinear Systems With Input Quantization","authors":"Long Gu, Lidong Wang, Xiaoping Liu, Aosen Zhang","doi":"10.1002/acs.70009","DOIUrl":"https://doi.org/10.1002/acs.70009","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, an adaptive neural network fixed-time control method based on command filtering is proposed for stochastic nonlinear systems with input quantization. The method utilizes a radial basis function neural network (RBFNN) to approximate the unknown nonlinear terms in the system. The jitter problem is effectively solved in the controller design by configuring the hysteresis quantization inputs as two bounded nonlinear functions. In addition, the fixed-time control strategy is combined with the command filtering method to probabilistically guarantee the fixed-time stability of the closed-loop system, which overcomes the “complexity explosion” and “singularity” problems in the classical backstepping design. Meanwhile, a new error compensation mechanism is designed to effectively compensate for the filtering error. The theoretical analysis proves that the control scheme can ensure that the output tracking error of the closed-loop system converges to a sufficiently small neighborhood of the origin in a fixed time and that all signals within the closed-loop system are bounded. Finally, the feasibility and effectiveness of the scheme are verified by two simulation examples.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 3","pages":"565-578"},"PeriodicalIF":3.8,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147570269","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}

引用次数: 0

Event-Triggered Optimal Control of Nonlinear Systems via Disturbance Observer-Based Reinforcement Learning Backstepping Approach 基于扰动观测器的非线性系统强化学习反步方法的事件触发最优控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-11-30 DOI: 10.1002/acs.70014

Ming-Yue Li, Bo Xu, Zhongsheng Hou

引用次数: 0

Predictive Optimal Iterative Learning Control for Nonlinear Systems Using the Koopman Operator 基于Koopman算子的非线性系统预测最优迭代学习控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-11-26 DOI: 10.1002/acs.70008

Xinyue Tao, Hongfeng Tao, Luyuan Gao, Wojciech Paszke, Eric Rogers

引用次数: 0

Adaptive Predefined-Time Control for High-Order Nonlinear Systems With Unmodeled Dynamics 具有未建模动力学的高阶非线性系统的自适应预定义时间控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-12-01 DOI: 10.1002/acs.70016

Lin Zhao, Shuai Sui, C. L. Philip Chen

引用次数: 0

Composite Learning Adaptive Optimized Backstepping Control for a Class of Nonlinear Strict-Feedback Systems With Prescribed Performance 一类具有规定性能的非线性严格反馈系统的复合学习自适应优化反步控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2026-03-16 Epub Date: 2025-12-03 DOI: 10.1002/acs.70018

Jian Wu, Yuanyuan Cheng, Dewen Cao

{"title":"Composite Learning Adaptive Optimized Backstepping Control for a Class of Nonlinear Strict-Feedback Systems With Prescribed Performance","authors":"Jian Wu, Yuanyuan Cheng, Dewen Cao","doi":"10.1002/acs.70018","DOIUrl":"https://doi.org/10.1002/acs.70018","url":null,"abstract":"<div>\u0000 \u0000 <p>To improve the learning efficiency of control strategies in uncertain systems, this paper proposes an adaptive neural network (NN) control method that synergizes optimized backstepping (OB) with a composite learning mechanism. Under the identifier-critic-actor architecture, we refine the identifier design by embedding a composite learning structure, where a NN with local approximation properties estimates system dynamics. The composite learning rate is constructed from both tracking and prediction errors, where the prediction error is generated based on a combination of online historical data and instantaneous measurements. A dynamically adjusted identifier learning rate optimizes NN weight updates, significantly improving approximation accuracy without requiring the persistent excitation (PE) condition. To solve the control problem of achieving prescribed-time convergence with predefined precision, a time-varying switching function and quartic barrier Lyapunov functions are designed to ensure tracking errors converge to a user-specified accuracy within a predetermined time frame, while guaranteeing closed-loop stability. Theoretical analysis confirms the uniform ultimate boundedness of all signals. Comparative simulations demonstrate that, compared to reinforcement learning-based OB control methods, the proposed approach achieves faster NN parameter convergence and superior approximation performance. Additionally, it exhibits lower control resource consumption than existing composite learning strategies.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 3","pages":"674-691"},"PeriodicalIF":3.8,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147562672","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}

引用次数: 0

Dynamics-Memory-Event-Based Adaptive Attitude Consensus Control for Multi-UAVs With Self-Adjusting Performance 基于动态记忆事件的多无人机自适应姿态一致性控制

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2025-11-21 DOI: 10.1002/acs.70003

Xinfeng Shao, Kewen Li

{"title":"Dynamics-Memory-Event-Based Adaptive Attitude Consensus Control for Multi-UAVs With Self-Adjusting Performance","authors":"Xinfeng Shao, Kewen Li","doi":"10.1002/acs.70003","DOIUrl":"https://doi.org/10.1002/acs.70003","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the attitude consensus control problem of a nonlinear unmanned aerial vehicle (UAV) attitude system subject to deferred performance constraints, external disturbance, and input saturation. The inherent nonlinearities and actuator saturation in UAV dynamics pose significant challenges to control design, particularly when performance guarantees are required under external disturbance and constrained control inputs. To address these challenges, we propose a novel intelligent adaptive fusion control method that incorporates a dynamic memory event-triggered mechanism (DMETM) to reduce communication and computational overhead while maintaining system stability and performance. A novel error-shifting mechanism is developed to overcome singularity challenges in deferred-constrained systems, accompanied by a non-singular funnel control strategy to ensure stable implementation of deferred constraint enforcement. By employing Lyapunov stability theory, the proposed approach effectively handles external disturbance and input saturation, ensuring that the UAV attitude system satisfies predefined performance criteria under these constraints. Finally, simulation results validate the efficacy of the proposed method, demonstrating its ability to achieve robust and efficient attitude control in realistic scenarios.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 2","pages":"456-467"},"PeriodicalIF":3.8,"publicationDate":"2025-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146256549","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}

引用次数: 0

Fault Estimation Based Control Design for Nonlinear Fractional-Order Systems Under Proportional-Integral Observer 比例积分观测器下基于故障估计的非线性分数阶系统控制设计

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2025-11-20 DOI: 10.1002/acs.70002

S. Sweetha, V. Panneerselvam, R. Sakthivel

{"title":"Fault Estimation Based Control Design for Nonlinear Fractional-Order Systems Under Proportional-Integral Observer","authors":"S. Sweetha, V. Panneerselvam, R. Sakthivel","doi":"10.1002/acs.70002","DOIUrl":"https://doi.org/10.1002/acs.70002","url":null,"abstract":"<div>\u0000 \u0000 <p>This study addresses the issue of finite-time observer-based <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>$$ {H}_{infty } $$</annotation>\u0000 </semantics></math> control design for a nonlinear fractional-order system under additive faults and disturbances. The main motive is to construct a nonlinear fractional-order proportional-integral observer such that it simultaneously estimates the states and fault signal. A controller is designed to overcome the mismatch between the quantization parameters, and also the estimated fault signal is incorporated in the control design to eliminate the effects of the fault in the system. Furthermore, by choosing an appropriate Lyapunov function, the results are deduced in terms of linear matrix inequalities, based on which the observer and controller gain values are obtained. Then the viability of the developed controller and observer is verified by numerical simulation results.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 2","pages":"444-455"},"PeriodicalIF":3.8,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146224283","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}

引用次数: 0

Distributed Fusion Filtering for Multi-Sensor Multi-Rate Systems With Packet Disorders Under Hybrid Cyber Attacks 混合网络攻击下多传感器多速率系统的分布式融合滤波

IF 3.8 4区计算机科学

International Journal of Adaptive Control and Signal Processing Pub Date : 2025-11-20 DOI: 10.1002/acs.70001

Pengyun Yue, Na Lin, Junhua Du, Ruonan Luo, Ruixue Zhang, Jun Hu

{"title":"Distributed Fusion Filtering for Multi-Sensor Multi-Rate Systems With Packet Disorders Under Hybrid Cyber Attacks","authors":"Pengyun Yue, Na Lin, Junhua Du, Ruonan Luo, Ruixue Zhang, Jun Hu","doi":"10.1002/acs.70001","DOIUrl":"https://doi.org/10.1002/acs.70001","url":null,"abstract":"<div>\u0000 \u0000 <p>This article investigates the distributed fusion (DF) filtering issue for multi-sensor multi-rate systems (MSMRSs) with packet disorders (PDs) under hybrid cyber attacks (HCAs). The PDs caused by random transmission delay are characterized by a random variable that has the known probability distribution, and two groups of Bernoulli random variables are adopted to depict the occurrence of HCAs. To facilitate the design of the filtering scheme, a virtual measurement method is introduced to transform the original multi-rate systems into single-rate systems. The purpose of this paper is to design a new local filtering scheme handling PDs, HCAs as well as stochastic nonlinearities simultaneously, and minimize the upper bound (UB) on each local filtering error covariance (LFEC) by selecting an appropriate gain matrix. By using the mathematical induction method, a sufficient condition is obtained to ensure that each LFEC is uniformly bounded. In addition, local estimates are fused based on the inverse covariance intersection (ICI) fusion method. Finally, it is shown that the proposed fusion filtering algorithm is effective through a simulation experiment.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 2","pages":"429-443"},"PeriodicalIF":3.8,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146256596","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}

引用次数: 0