International Journal of Adaptive Control and Signal Processing最新文献

{"title":"A Distributed Actor-Critic Learning Approach for Affine Formation Control of Multi-Robots With Unknown Dynamics","authors":"Ronghua Zhang,&nbsp;Qingwen Ma,&nbsp;Xinglong Zhang,&nbsp;Xin Xu,&nbsp;Daxue Liu","doi":"10.1002/acs.3972","DOIUrl":"https://doi.org/10.1002/acs.3972","url":null,"abstract":"<div>\u0000 \u0000 <p>Formation maneuverability is particularly important for multi-robots (MRs), especially when the robots are operating cooperatively in complex and dynamic environments. Although various methods have been developed for affine formation, it is still a difficult problem to design an affine formation controller for MRs with unknown dynamics. In this paper, a distributed actor-critic learning approach (DACL) in a look-ahead rollout manner is proposed for the affine formation of MRs under local communication, which improves the online learning efficiency. In the proposed approach, a distributed data-driven online optimization mechanism is designed via the sparse kernel technique to solve the near-optimal affine formation control issue of MRs with unknown dynamics as well as improve control performance. The unknown dynamics of MRs are learned offline based on precollected input-output datasets, and the sparse kernel-based approach is employed to increase the feature representation capability of the samples. Then, the proposed distributed online actor-critic algorithm for each robot in the formation includes two neural networks, which are utilized to approximate the costate functions and the near-optimal policies. Moreover, the convergence analysis of the proposed approach has been conducted. Finally, numerical simulation and KKSwarm-based experiment studies are performed to verify the effectiveness of the proposed approach.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"803-817"},"PeriodicalIF":3.9,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818807","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":"Cross-Scale Imperfect Data-Based Composite \u0000 \u0000 \u0000 \u0000 \u0000 H\u0000 \u0000 \u0000 ∞\u0000 \u0000 \u0000 \u0000 $$ {H}_{infty } $$\u0000 Control of Nonlinear Two-Time-Scale Systems","authors":"Xiaomin Liu,&nbsp;Mengjun Yu,&nbsp;Kun Feng,&nbsp;Gonghe Li,&nbsp;Linna Zhou,&nbsp;Haoyu Wang,&nbsp;Chunyu Yang","doi":"10.1002/acs.3974","DOIUrl":"https://doi.org/10.1002/acs.3974","url":null,"abstract":"<div>\u0000 \u0000 <p>Utilizing the cross-scale imperfect data, the reinforcement learning (RL) composite <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 of nonlinear two-time-scale (TTS) systems is proposed in the presence of unknown slow dynamics. First, with the feat of singular perturbation theory (SPT), the original <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 problem is decomposed and rearranged into standard fast and slow subproblems that have no cross terms between state, control and disturbance in the performance indices. Then, since the states of decomposed fast and slow subsystems cannot be measured perfectly, the state reconstruction mechanism is proposed based on the input-state data of the original system, and cross-scale information interaction is incorporated to correct the bias induced by the time-scale decomposition. Cross-scale composite RL algorithm is proposed with the <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> slow and fast controllers designed in separate time scales. Next, the stability and <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> performance of the TTS systems under the composite controller is analyzed considering the data inaccuracy of state reconstruction. Finally, the effectiveness of the proposed method is validated in the control application to the permanent magnet synchronous motor (PMSM) system.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"745-760"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818795","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":"Distributed Filtering for State-Saturated Systems With Switching Nonlinearities via Rayleigh Fading Channels: An Adaptive Event-Triggered Case","authors":"Qingbo Zhang,&nbsp;Jun Hu,&nbsp;Desheng Liu,&nbsp;Mingqing Zhu,&nbsp;Hui Yu","doi":"10.1002/acs.3978","DOIUrl":"https://doi.org/10.1002/acs.3978","url":null,"abstract":"<div>\u0000 \u0000 <p>The distributed filtering (DF) problem is investigated for state-saturated systems (SSSs) with switching nonlinearities under the adaptive event-triggered mechanism (AETM) and Rayleigh fading channels over sensor networks, where the data is transmitted between nodes through the Rayleigh fading channel. In addition, the AETM is introduced to save communication resources and improve data transmission efficiency. First, a distributed filter is designed incorporating the information of state saturation, switching nonlinearity, Rayleigh fading channel and AETM. Second, the upper bound (UB) on the filtering error covariance (FEC) is derived by the mathematical induction method, and the filter gain is obtained by minimizing the trace of the UB. Subsequently, the boundedness of UB on the FEC is shown through mathematical analysis. Finally, the effectiveness of the filtering scheme designed in this article is demonstrated through a numerical simulation example and a practical example, in which the influence of different Rayleigh parameters to the filtering performance and the superiority of using the AETM are discussed.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"785-802"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818783","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":"Dissipative Synchronization Control for Two-Time-Scale Markov Jump Neural Networks Subject to Redundant Channels: A Hidden-Markov-Model-Based Method","authors":"Yongqian Wang,&nbsp;Zhenghao Ni,&nbsp;Kang Wang,&nbsp;Feng Li,&nbsp;Hao Shen","doi":"10.1002/acs.3975","DOIUrl":"https://doi.org/10.1002/acs.3975","url":null,"abstract":"<div>\u0000 \u0000 <p>This work studies the synchronization issue for two-time-scale Markov jump neural networks subject to redundant channels. In such systems, mode information may not be directly available (e.g., packet loss), and traditional synchronous control methods cannot meet this challenge. The hidden Markov model can deal with the situation that the systems state cannot be accessed directly, and estimate the current state of the system through the “observation” mode, so as to improve the controller design and advance the stability and robustness of the systems. Therefore, the controller is designed based on a hidden Markov model for the above scenarios. Meanwhile, the redundant channels are built to reduce the influence of packet loss. Moreover, the two-time-scale phenomenon of the plant is considered by using the singular perturbation parameter. Then, the Lyapunov function construction is associated with the singular perturbation parameter and some sufficient conditions to guarantee the stability of the plant are obtained. Finally, the designed control law is available which is demonstrated by two illustrative examples.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"761-771"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818782","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":"Vibration Suppression and Adaptive Fault-Tolerant Control for Three-Dimensional Flexible Rotating Manipulator With Input Signal Constraints","authors":"Jiacheng Wang,&nbsp;Qingzhen Zhang,&nbsp;Jinkun Liu,&nbsp;Xing Chen,&nbsp;Cenbo Xue","doi":"10.1002/acs.3964","DOIUrl":"https://doi.org/10.1002/acs.3964","url":null,"abstract":"<div>\u0000 \u0000 <p>Based on a three-dimensional flexible, rotating manipulator, this paper is dedicated to the issue of vibration suppression and angle planning subject to actuator failures and input signal constraints. Considering that a flexible link belongs to a distributed parameter system, the motion model is obtained by Hamilton's principle and described by partial differential equations (PDEs). A novel fault-tolerant control law is proposed to eliminate the elastic deflection and vibration of the flexible link and to follow the desired angle of the rotating base and the manipulator with the appearance of actuator failures. The adaptive operator based on projection mapping is adopted to estimate the loss of the actuator. In addition, the hyperbolic tangent function is employed to constrain the input signal so that it is within an adjustable interval. The Lyapunov's method and LaSalle invariance principle are applied to prove the stability and convergence of the closed-loop system. The simulation results are provided to demonstrate the effectiveness of the proposed method.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"736-744"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818618","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":"Multi-Dimensional Taylor Network-Based Adaptive Tracking Control for Nonlinear Time-Delay Systems Subject to Asymmetric Input Saturation Under Prescribed Performance","authors":"Lian-Lian Zhai,&nbsp;Wei Zhao,&nbsp;Ya-Feng Zhou,&nbsp;Yu-Qun Han","doi":"10.1002/acs.3977","DOIUrl":"https://doi.org/10.1002/acs.3977","url":null,"abstract":"<div>\u0000 \u0000 <p>The objective of this study is to develop a new control method for nonlinear time-delay systems with input saturation and to achieve the prescribed performance control target by exploiting the excellent approximation performance of multidimensional Taylor networks (MTNs). The transformation method is used to transform the complex saturation model into a simple model with bounded error, simplifying the controller design process. The MTN is used to handle the nonlinear functions of the system, and an original adaptive control algorithm is constructed with the help of the backstepping method. The proposed control approach is feasible and can implement the tracking error signal that falls into the desired prescribed scope with all the signals in the control system being bounded. Finally, the efficiency of the proposed approach is demonstrated by presenting simulation results.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"772-784"},"PeriodicalIF":3.9,"publicationDate":"2025-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818619","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":"Variable Step-Size LMS Algorithm Based on Variational Versoria Function and Variational Gaussian Function","authors":"Baoshui Zhao,&nbsp;Yancai Xiao,&nbsp;Haikuo Shen,&nbsp;Shaodan Zhi","doi":"10.1002/acs.3970","DOIUrl":"https://doi.org/10.1002/acs.3970","url":null,"abstract":"<div>\u0000 \u0000 <p>Aiming at the noise interference problem in wing fatigue tests, this paper improves the traditional LMS algorithm using the variational Versoria function and the variational Gaussian function. Additionally, this paper proposes a variable step-size LMS (VSS-LMS) filtering algorithm based on the composite function (CVSS-LMS). The composite function combines the variational Versoria function and the variational Gaussian function to describe the nonlinear relationship between the iteration step size and the error. To adapt to environments with different signal-to-noise ratios, the algorithm replaces the fixed parameters with a combination of current and previous errors, thus enabling adaptive adjustment of the parameters. Moreover, a step-size dynamic constraint rule is proposed to further improve the stability of the algorithm. The algorithm is normalized using a combination of the cumulative sum of error squares, the mean square error (MSE), and the power of the input signal, which reduces the sensitivity to the input signal amplitude. The above parts finally constitute the adaptive CVSS-LMS (ACVSS-LMS) filtering algorithm. The convergence of the ACVSS-LMS algorithm is verified through theoretical derivation. The ACVSS-LMS algorithm is experimentally analyzed by using the simulation data generated by MATLAB and the actual data collected from the wing fatigue test, and the results show that the ACVSS-LMS algorithm proposed in this paper has a faster convergence speed and lower steady-state error compared to other algorithms.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"709-723"},"PeriodicalIF":3.9,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818818","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":"MTN-Based Adaptive Finite-Time Tracking Control for Switched Non-Linear Systems With Time-Varying State Function Constraints","authors":"Jing-Jing Sun,&nbsp;Shan-Liang Zhu,&nbsp;Yao-Yao Guo,&nbsp;Yu-Qun Han","doi":"10.1002/acs.3973","DOIUrl":"https://doi.org/10.1002/acs.3973","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper studies the finite-time control problem of a class of switched non-linear systems under time-varying state constraints and proposes an adaptive finite-time controller based on a multi-dimensional Taylor network (MTN). Firstly, the time-varying tangent barrier Lyapunov functions (TBLFs) are constructed to ensure that all system states are constrained within a certain range. Secondly, MTNs are used to estimate the unknown non-linear functions during the controller design process. The proposed control scheme ensures that the tracking error of the system can converge to a small domain of the origin in a finite-time. At the same time, all the signals of the closed-loop system are semi-global practical finite-time stable (SGPFS) and all states satisfy the defined time-varying state constraints. Finally, the effectiveness of the control strategy is verified through numerical simulation examples and practical simulation examples.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"724-735"},"PeriodicalIF":3.9,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818819","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":"Scalable \u0000 \u0000 \u0000 δ\u0000 \u0000 $$ delta $$\u0000 -Level Coherent State Synchronization of Multi-Agent Systems with Adaptive Protocols and Bounded Disturbances","authors":"Donya Nojavanzadeh,&nbsp;Zhenwei Liu,&nbsp;Ali Saberi,&nbsp;Anton A. Stoorvogel","doi":"10.1002/acs.3953","DOIUrl":"https://doi.org/10.1002/acs.3953","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, we study scalable <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>δ</mi>\u0000 </mrow>\u0000 <annotation>$$ delta $$</annotation>\u0000 </semantics></math>-level coherent state synchronization for multi-agent systems (MAS) where the agents are subject to bounded disturbances/noises. We propose a scale-free framework designed solely based on the knowledge of agent models and agnostic to the communication graph and the size of the network. We define the level of coherency for each agent as the norm of the weighted sum of the disagreement dynamics with its neighbors. The objective is to restrict the network's coherency level to <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>δ</mi>\u0000 </mrow>\u0000 <annotation>$$ delta $$</annotation>\u0000 </semantics></math> without a-priori information about the disturbance.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 3","pages":"497-516"},"PeriodicalIF":3.9,"publicationDate":"2025-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622410","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":"Ocean Currents Compensation-Based IAILOS-ROESOs Guidance and Adaptive Sliding Mode Path Following Control for Unmanned Surface Vehicles","authors":"Huang Zhang,&nbsp;Zhiping He,&nbsp;Guofeng Wang,&nbsp;Yunsheng Fan,&nbsp;Baojian Song","doi":"10.1002/acs.3966","DOIUrl":"https://doi.org/10.1002/acs.3966","url":null,"abstract":"<div>\u0000 \u0000 <p>This article studies the problem of path following for unmanned surface vehicles (USVs) with ocean currents and input saturation and proposes an ocean currents compensation-based improved adaptive integral line-of-sight with reduced-order expanded state observers (IAILOS-ROESOs) guidance and adaptive integral sliding mode control (AISMC) compound guidance-control method. In the guidance module, an IAILOS-ROESOs guidance law is presented to estimate ocean currents of varying strengths, compensating for the effects of ocean currents at the kinematics level. Then, the AISMC law with the RBF neural network and parameter update law are introduced to approximate the lumped disturbances and estimate their bounds of the estimation error in the control module. Meanwhile, integrating nonlinear differential estimators and improved auxiliary dynamic systems with a smoothly switching function, achieves the differential signal filtering and input saturation, and the hyperbolic tangent saturation function with adjustable parameters is further used to improve the robustness of the system. Theoretical analysis indicates that all errors converge to zero. Finally, the effectiveness of the control strategy is verified through comparative simulations.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"39 4","pages":"692-708"},"PeriodicalIF":3.9,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818682","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}