Security is of paramount importance in the operation of human‐controlled mechanical systems. In the unfortunate event of an accident, the operator may find themselves in a state of distress. This research focuses on the study of adaptive event‐triggered shared control techniques for uncertain Euler–Lagrange systems afflicted by actuator faults and the presence of unknown disturbances. Unlike existing results on shared control, the uncertain Euler–Lagrange system considered in this study contains both an unknown control direction and actuator faults, making it more practical. Furthermore, the controller we have designed demonstrates enhanced stability in the face of these challenges. To counteract the impact of unknown control direction, we introduce a state feedback controller employing Nussbaum functions. Additionally, the devised event‐triggered mechanism serves to reduce the system's network communication resource utilization. The implementation of our shared control strategy ensures asymptotic tracking of target trajectories by the system's outputs while maintaining consistent operation within a defined safe region. Finally, a simulated example is presented to validate the effectiveness of our proposed methodologies.
{"title":"Event‐triggered shared control for Euler–Lagrange systems with actuator fault and unknown control direction","authors":"Xiaoying Feng, Xiaoyu Zhang","doi":"10.1002/asjc.3496","DOIUrl":"https://doi.org/10.1002/asjc.3496","url":null,"abstract":"Security is of paramount importance in the operation of human‐controlled mechanical systems. In the unfortunate event of an accident, the operator may find themselves in a state of distress. This research focuses on the study of adaptive event‐triggered shared control techniques for uncertain Euler–Lagrange systems afflicted by actuator faults and the presence of unknown disturbances. Unlike existing results on shared control, the uncertain Euler–Lagrange system considered in this study contains both an unknown control direction and actuator faults, making it more practical. Furthermore, the controller we have designed demonstrates enhanced stability in the face of these challenges. To counteract the impact of unknown control direction, we introduce a state feedback controller employing Nussbaum functions. Additionally, the devised event‐triggered mechanism serves to reduce the system's network communication resource utilization. The implementation of our shared control strategy ensures asymptotic tracking of target trajectories by the system's outputs while maintaining consistent operation within a defined safe region. Finally, a simulated example is presented to validate the effectiveness of our proposed methodologies.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"7 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186309","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}
Jawhar Ghommam, Lamia Iftekhar, Mohammad H. Rahman, Maarouf Saad
SummaryIn this paper, a new approach for formation‐containment control with prescribed performances is introduced for heterogeneous autonomous vehicles involving a cluster of leader unmanned aerial vehicles (UAVs) and follower unmanned surface vessels (USVs). We introduce a two‐layer distributed control system: The upper layer focuses on guiding the UAVs to form a scalable lattice while synchronizing their movement along a predefined path, and the second layer guides the USVs to enter the convex hull formed by the UAVs, ensuring collision‐free operation with static/dynamic objects. To prevent collisions and ensure lattice formation, a set of well‐defined bump functions are utilized in the design of the backstepping control algorithm. Managing virtual controls, we incorporate a nonlinear dynamic surface control (NDSC), while a universal barrier function enhances the convergence of formation tracking errors. Furthermore, each USV employs a cooperative adaptive learning neural network to handle uncertainties in heterogeneous vehicle models. Utilizing the Lyapunov theorem, the stability of the formation‐containment of UAV/USV is achieved, and all signals in the formation‐containment systems are semiglobal uniform ultimate bounded (SGUUB). A simulation example showcases the effectiveness of our proposed approach, highlighting contributions in collision avoidance, synchronization speed, and adaptive learning. Our work advances the heterogeneous formation‐containment literature towards more realistic scenarios with safety‐critical considerations amidst multiple layers of uncertainties and unknown parameters.
{"title":"Cooperative learning‐based practical formation‐containment control with prescribed performance for heterogeneous clusters of UAV/USV","authors":"Jawhar Ghommam, Lamia Iftekhar, Mohammad H. Rahman, Maarouf Saad","doi":"10.1002/asjc.3480","DOIUrl":"https://doi.org/10.1002/asjc.3480","url":null,"abstract":"SummaryIn this paper, a new approach for formation‐containment control with prescribed performances is introduced for heterogeneous autonomous vehicles involving a cluster of leader unmanned aerial vehicles (UAVs) and follower unmanned surface vessels (USVs). We introduce a two‐layer distributed control system: The upper layer focuses on guiding the UAVs to form a scalable lattice while synchronizing their movement along a predefined path, and the second layer guides the USVs to enter the convex hull formed by the UAVs, ensuring collision‐free operation with static/dynamic objects. To prevent collisions and ensure lattice formation, a set of well‐defined bump functions are utilized in the design of the backstepping control algorithm. Managing virtual controls, we incorporate a nonlinear dynamic surface control (NDSC), while a universal barrier function enhances the convergence of formation tracking errors. Furthermore, each USV employs a cooperative adaptive learning neural network to handle uncertainties in heterogeneous vehicle models. Utilizing the Lyapunov theorem, the stability of the formation‐containment of UAV/USV is achieved, and all signals in the formation‐containment systems are semiglobal uniform ultimate bounded (SGUUB). A simulation example showcases the effectiveness of our proposed approach, highlighting contributions in collision avoidance, synchronization speed, and adaptive learning. Our work advances the heterogeneous formation‐containment literature towards more realistic scenarios with safety‐critical considerations amidst multiple layers of uncertainties and unknown parameters.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"18 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186317","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}
Ming‐Rui Liu, Li‐Bing Wu, Ming Chen, Guo‐Fei Cui, Qi Chen
SummaryThis article investigates a model‐based event‐triggered adaptive leaderless consensus control problem for one category of nonlinear pure‐feedback multi‐agent systems (MASs). The implicit function‐based median theorem for decoupling is applied to deal with the over‐fuzzy as well as feedback linearization issues. The feature extraction approach is introduced to solve the difficulty of unequal dimensionality of variables due to the inter‐agents information interaction. Then, by constructing the corresponding adaptive model and utilizing event‐based neural network (NN), a novel distributed design methodology for MAS‐based control input and agent weight‐based dynamic triggering threshold is presented. Through the impulse‐based Lyapunov theory analysis, the designed strategy not just guarantees the stability of the proposed system but then also ensures the boundedness of all signals within the closed‐loop system. Eventually, after verifying the absence of Zeno behavior and ensuring the achievement of the desired consensus tracking, the usefulness of the developed control scheme is justified by a numerical simulation instance.
摘要 本文研究了一类非线性纯反馈多代理系统（MAS）的基于模型的事件触发自适应无领导共识控制问题。应用基于隐函数的中值定理进行解耦，以解决过度模糊和反馈线性化问题。引入了特征提取方法，以解决因代理间信息交互而导致的变量不等维度的难题。然后，通过构建相应的自适应模型并利用基于事件的神经网络（NN），提出了一种基于 MAS 的控制输入和基于代理权重的动态触发阈值的新型分布式设计方法。通过基于脉冲的 Lyapunov 理论分析，所设计的策略不仅保证了拟议系统的稳定性，还确保了闭环系统内所有信号的有界性。最后，在验证不存在芝诺行为并确保实现所需的共识跟踪后，通过数值模拟实例证明了所开发控制方案的实用性。
{"title":"Model‐based event‐triggered leaderless consensus control for nonlinear pure‐feedback multi‐agent systems","authors":"Ming‐Rui Liu, Li‐Bing Wu, Ming Chen, Guo‐Fei Cui, Qi Chen","doi":"10.1002/asjc.3486","DOIUrl":"https://doi.org/10.1002/asjc.3486","url":null,"abstract":"SummaryThis article investigates a model‐based event‐triggered adaptive leaderless consensus control problem for one category of nonlinear pure‐feedback multi‐agent systems (MASs). The implicit function‐based median theorem for decoupling is applied to deal with the over‐fuzzy as well as feedback linearization issues. The feature extraction approach is introduced to solve the difficulty of unequal dimensionality of variables due to the inter‐agents information interaction. Then, by constructing the corresponding adaptive model and utilizing event‐based neural network (NN), a novel distributed design methodology for MAS‐based control input and agent weight‐based dynamic triggering threshold is presented. Through the impulse‐based Lyapunov theory analysis, the designed strategy not just guarantees the stability of the proposed system but then also ensures the boundedness of all signals within the closed‐loop system. Eventually, after verifying the absence of Zeno behavior and ensuring the achievement of the desired consensus tracking, the usefulness of the developed control scheme is justified by a numerical simulation instance.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"58 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186313","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}
Idael Oliva‐Leal, Jorge Said Cervantes‐Rojas, Rogelio Lozano, Iván González‐Hernández
This study presents a novel design of an optimized chattering‐attenuated quasi‐sliding mode controller for the stabilization of a vertical take‐off and landing aircraft affected by external disturbances. We propose a methodology based on a particle swarm optimization algorithm to provide an optimal boundary layer thickness of the quasi‐sliding mode controller (QSMC) structure based on a sigmoid‐type function approximation to reduce the chattering noise in the control signal while an adequate stabilization quality is guaranteed. This represents an alternative to the common strategies based on a trial and error tuning of such boundary layer thickness of sigmoid‐type approximations. Also, the Lyapunov formalism is applied to restrict the search space of the QSMC gain to guarantee stability conditions. Some simulation tests were carried out to demonstrate the enhanced chattering attenuation capability of the proposed solution against a standard sliding mode controller and the superior stabilization performance versus other robust controllers.
{"title":"Optimized chattering‐attenuated sliding mode controller for a perturbed VTOL system","authors":"Idael Oliva‐Leal, Jorge Said Cervantes‐Rojas, Rogelio Lozano, Iván González‐Hernández","doi":"10.1002/asjc.3492","DOIUrl":"https://doi.org/10.1002/asjc.3492","url":null,"abstract":"This study presents a novel design of an optimized chattering‐attenuated quasi‐sliding mode controller for the stabilization of a vertical take‐off and landing aircraft affected by external disturbances. We propose a methodology based on a particle swarm optimization algorithm to provide an optimal boundary layer thickness of the quasi‐sliding mode controller (QSMC) structure based on a sigmoid‐type function approximation to reduce the chattering noise in the control signal while an adequate stabilization quality is guaranteed. This represents an alternative to the common strategies based on a trial and error tuning of such boundary layer thickness of sigmoid‐type approximations. Also, the Lyapunov formalism is applied to restrict the search space of the QSMC gain to guarantee stability conditions. Some simulation tests were carried out to demonstrate the enhanced chattering attenuation capability of the proposed solution against a standard sliding mode controller and the superior stabilization performance versus other robust controllers.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"2 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224419","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}
Fuel cell stack (FCS) is a practical power source for new energy vehicle applications, and fuel economy is a problem that many researchers are concerned about. In this paper, an adaptive real‐time control strategy aiming at improving fuel efficiency is proposed; the control purpose is to distribute the power requirement between the FCS and the battery to achieve good fuel economy. First, the FCS model is built according to experiment data, and in order to reflect the affection of the temperature to the proposed control strategy, the thermal model of the battery is established. Then the future power requirement is predicted via Bayes inference analysis. Based on the FCS model, the battery model, and the predicted power requirement, the real‐time control strategy is designed and solved with minimization principle optimization over the receding horizon. The proposed control strategy is validated both through simulation and hardware‐in‐loop (Hil) experiments on a 40 kW FCS. The results compared with the rule‐based (RB) strategy and the loss minimum strategy (LMS) show that the proposed control strategy can effectively reduce fuel consumption by 4%, and at the same time, it can help extend the life span of the battery by considering the temperature affection.
{"title":"Adaptive optimal control strategy of fuel economy for fuel cell battery storage system using in HEV applications","authors":"Jiangtao Fu, Yulin Fu, Zhumu Fu, Shuzhong Song","doi":"10.1002/asjc.3490","DOIUrl":"https://doi.org/10.1002/asjc.3490","url":null,"abstract":"Fuel cell stack (FCS) is a practical power source for new energy vehicle applications, and fuel economy is a problem that many researchers are concerned about. In this paper, an adaptive real‐time control strategy aiming at improving fuel efficiency is proposed; the control purpose is to distribute the power requirement between the FCS and the battery to achieve good fuel economy. First, the FCS model is built according to experiment data, and in order to reflect the affection of the temperature to the proposed control strategy, the thermal model of the battery is established. Then the future power requirement is predicted via Bayes inference analysis. Based on the FCS model, the battery model, and the predicted power requirement, the real‐time control strategy is designed and solved with minimization principle optimization over the receding horizon. The proposed control strategy is validated both through simulation and hardware‐in‐loop (Hil) experiments on a 40 kW FCS. The results compared with the rule‐based (RB) strategy and the loss minimum strategy (LMS) show that the proposed control strategy can effectively reduce fuel consumption by 4%, and at the same time, it can help extend the life span of the battery by considering the temperature affection.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"5 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186314","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}
Lin He, Ziang Xu, Yujiang Wei, Mingwei Wang, Chunrong Huang, Qin Shi
The sliding mode control has to design a sliding manifold for manipulating the system motion in engineering practice, making system asymptotic stability paramount. This is particularly challenging for using variable sliding manifold parameters to formulate the sliding manifold for fast convergence and precise control. While much of the research on sliding mode control has focused on constant sliding manifold parameters, comparatively little is known about the variable approach of the sliding manifold parameters. Therefore, sliding manifold parameters are treated as variables and are computed by a parameter tuning algorithm. Regarding the parameter tuning algorithm, its input is the sliding mode control law with variable sliding manifold parameters, and its output is the computed sliding manifold parameters that will be transmitted back to the sliding mode control law. Through tuning the sliding manifold parameters by an optimal method of lowest cost with the measuring value and model computing value of system states based on the historical information, the difference between the nominal model and the real system will be removed. Here we discuss a series of studies on the algorithm of tune sliding control that, collectively, develop an application of how the tune sliding controller steers the front wheels of the full self-driving vehicle. The designed approach has been tested in a steering test vehicle to realize a good angle tracking performance of the electric motor steer-by-wire system.
{"title":"A tune sliding control algorithm for angle following of electric motor steer-by-wire system","authors":"Lin He, Ziang Xu, Yujiang Wei, Mingwei Wang, Chunrong Huang, Qin Shi","doi":"10.1002/asjc.3487","DOIUrl":"https://doi.org/10.1002/asjc.3487","url":null,"abstract":"The sliding mode control has to design a sliding manifold for manipulating the system motion in engineering practice, making system asymptotic stability paramount. This is particularly challenging for using variable sliding manifold parameters to formulate the sliding manifold for fast convergence and precise control. While much of the research on sliding mode control has focused on constant sliding manifold parameters, comparatively little is known about the variable approach of the sliding manifold parameters. Therefore, sliding manifold parameters are treated as variables and are computed by a parameter tuning algorithm. Regarding the parameter tuning algorithm, its input is the sliding mode control law with variable sliding manifold parameters, and its output is the computed sliding manifold parameters that will be transmitted back to the sliding mode control law. Through tuning the sliding manifold parameters by an optimal method of lowest cost with the measuring value and model computing value of system states based on the historical information, the difference between the nominal model and the real system will be removed. Here we discuss a series of studies on the algorithm of tune sliding control that, collectively, develop an application of how the tune sliding controller steers the front wheels of the full self-driving vehicle. The designed approach has been tested in a steering test vehicle to realize a good angle tracking performance of the electric motor steer-by-wire system.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"13 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186316","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}
The problem of recursive set-membership filter design for two-dimensional (2-D) systems subject to FlexRay communication protocol and hybrid cyber attacks (HCAs) is investigated in this article. The FlexRay protocol that integrates time-triggered and event-triggered mechanisms and involves a series of pre-defined communication cycles based on bidirectional metrics is developed to alleviate the network bandwidth load. Furthermore, the envisioned system is exposed to false data injection and denial-of-service attacks that occur in a randomized manner. Subsequently, the dynamic filtering error system (FES) subject to bidirectional evolutionary HCAs and FlexRay scheduling protocol is constructed. Then, sufficient conditions are obtained such that the dynamic FES consistently resides within an ellipsoidal set by utilizing double mathematical induction and recursive linear matrix inequalities (RLMIs). Moreover, the optimal filtering algorithm is given by minimizing the ellipsoidal constraints from the perspective of the traces of the matrix. The effectiveness of the presented recursive set-membership filter design approach is validated by a long-distance transmission line example.
{"title":"Recursive set-membership filtering for two-dimensional shift-varying systems with FlexRay protocol and hybrid cyber attacks","authors":"Pan Zhang, Chaoqun Zhu, Zhiwen Wang, Bin Yang","doi":"10.1002/asjc.3478","DOIUrl":"https://doi.org/10.1002/asjc.3478","url":null,"abstract":"The problem of recursive set-membership filter design for two-dimensional (2-D) systems subject to FlexRay communication protocol and hybrid cyber attacks (HCAs) is investigated in this article. The FlexRay protocol that integrates time-triggered and event-triggered mechanisms and involves a series of pre-defined communication cycles based on bidirectional metrics is developed to alleviate the network bandwidth load. Furthermore, the envisioned system is exposed to false data injection and denial-of-service attacks that occur in a randomized manner. Subsequently, the dynamic filtering error system (FES) subject to bidirectional evolutionary HCAs and FlexRay scheduling protocol is constructed. Then, sufficient conditions are obtained such that the dynamic FES consistently resides within an ellipsoidal set by utilizing double mathematical induction and recursive linear matrix inequalities (RLMIs). Moreover, the optimal filtering algorithm is given by minimizing the ellipsoidal constraints from the perspective of the traces of the matrix. The effectiveness of the presented recursive set-membership filter design approach is validated by a long-distance transmission line example.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"20 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186315","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}
In this paper, trajectory tracking control is investigated for a wheeled mobile robot with one unpowered trailer using an extended state observer (ESO). The unpowered trailer is added to improve load capacity, which results in a large impact on trajectory tracking as a slow‐varying and large disturbance. A backstepping controller is proposed to generate desired velocities in an outer loop of a double closed‐loop structure. The ESO is employed in an inner loop to estimate the slow‐varying and large disturbance from the unpowered trailer. An integral sliding mode controller is also designed in the inner loop to track the desired velocities from the outer loop. Stability analysis for the ESO, the backstepping controller and the integral sliding mode controller is conducted via Lyapunov methods. Simulation results are provided to show the effectiveness of the trajectory tracking control for a wheeled mobile robot with one unpowered trailer.
{"title":"Extended state observer‐based trajectory tracking control of a wheeled mobile robot with one unpowered trailer","authors":"Hongjiu Yang, Ran Dang, Peng Li","doi":"10.1002/asjc.3489","DOIUrl":"https://doi.org/10.1002/asjc.3489","url":null,"abstract":"In this paper, trajectory tracking control is investigated for a wheeled mobile robot with one unpowered trailer using an extended state observer (ESO). The unpowered trailer is added to improve load capacity, which results in a large impact on trajectory tracking as a slow‐varying and large disturbance. A backstepping controller is proposed to generate desired velocities in an outer loop of a double closed‐loop structure. The ESO is employed in an inner loop to estimate the slow‐varying and large disturbance from the unpowered trailer. An integral sliding mode controller is also designed in the inner loop to track the desired velocities from the outer loop. Stability analysis for the ESO, the backstepping controller and the integral sliding mode controller is conducted via Lyapunov methods. Simulation results are provided to show the effectiveness of the trajectory tracking control for a wheeled mobile robot with one unpowered trailer.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"32 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186318","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}
This paper proposes a fixed‐time convergence adaptive sliding mode fault‐tolerant controller (ASFTC) to address the air cushion vehicle (ACV) trajectory tracking problem under unknown environmental disturbances and actuator faults. The introduced method enhances the robustness and reduces the chattering of the controller, by proposing an initial state‐independent fixed‐time convergence method combined with a global sliding mode surface which has the advantage of quickly reaching the “sliding mode”. The model knowledge neural network (MKNN) method is employed to eliminate uncertain parameter effects, and it adjusts disturbance and fault estimates in real time based on tracking errors without the need for upper‐bound disturbance information and additional observer compensation. Finally, simulations validate the effectiveness of the proposed adaptive fault‐tolerant control system.
{"title":"Adaptive fault‐tolerant control for air cushion vehicle with fixed‐time convergence","authors":"Bai Dan, Fu Mingyu, Deng Hanbo, Wang Qiusu","doi":"10.1002/asjc.3452","DOIUrl":"https://doi.org/10.1002/asjc.3452","url":null,"abstract":"This paper proposes a fixed‐time convergence adaptive sliding mode fault‐tolerant controller (ASFTC) to address the air cushion vehicle (ACV) trajectory tracking problem under unknown environmental disturbances and actuator faults. The introduced method enhances the robustness and reduces the chattering of the controller, by proposing an initial state‐independent fixed‐time convergence method combined with a global sliding mode surface which has the advantage of quickly reaching the “sliding mode”. The model knowledge neural network (MKNN) method is employed to eliminate uncertain parameter effects, and it adjusts disturbance and fault estimates in real time based on tracking errors without the need for upper‐bound disturbance information and additional observer compensation. Finally, simulations validate the effectiveness of the proposed adaptive fault‐tolerant control system.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"25 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186321","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}
In this article, we explore the group output tracking consensus problem for discrete‐time strict‐feedback ‐order nonlinear multiagent systems that run repeatedly on finite time . A novel distributed adaptive iterative learning group consensus protocol is designed, which consists of two main components. The first component is based on time‐varying neural networks, which is used to approximate the unknown nonlinear function in the ‐step ahead predictor. In general, not all followers can access the information regarding the leader, which complicates the design of iterative learning protocols for MASs. Therefore, the second component of the protocol addresses this challenge by treating the leader's output as a time‐varying parameter and designing a time‐varying auxiliary term to compensate the leader's output information. Parameter updating laws and initial state learning laws are also proposed via the cooperative‐competitive relationship between the agents. We demonstrate the group consensus with sufficient small errors can be achieved at time , as the number of iterations proceed to infinity. Then, the results are extended to the case of multisubgroups and multileaders. Finally, two simulations validate the findings of this article.
本文探讨了在有限时间内重复运行的离散-时严格反馈-阶非线性多代理系统的群体输出跟踪共识问题。我们设计了一种新颖的分布式自适应迭代学习小组共识协议，它由两个主要部分组成。第一个部分基于时变神经网络，用于近似超前预测器中的未知非线性函数。一般来说，并非所有追随者都能获取领导者的信息，这使得 MAS 的迭代学习协议设计变得复杂。因此，协议的第二部分将领导者的输出视为时变参数，并设计一个时变辅助项来补偿领导者的输出信息，从而解决了这一难题。我们还通过代理之间的合作竞争关系提出了参数更新法则和初始状态学习法则。然后，我们将结果扩展到多分组和多领导的情况。最后，两个模拟验证了本文的结论。
{"title":"Adaptive learning control for group consensus tracking of discrete nonlinear multiagent systems","authors":"Qianhui Gao, Jinsha Li, Junmin Li","doi":"10.1002/asjc.3477","DOIUrl":"https://doi.org/10.1002/asjc.3477","url":null,"abstract":"In this article, we explore the group output tracking consensus problem for discrete‐time strict‐feedback ‐order nonlinear multiagent systems that run repeatedly on finite time . A novel distributed adaptive iterative learning group consensus protocol is designed, which consists of two main components. The first component is based on time‐varying neural networks, which is used to approximate the unknown nonlinear function in the ‐step ahead predictor. In general, not all followers can access the information regarding the leader, which complicates the design of iterative learning protocols for MASs. Therefore, the second component of the protocol addresses this challenge by treating the leader's output as a time‐varying parameter and designing a time‐varying auxiliary term to compensate the leader's output information. Parameter updating laws and initial state learning laws are also proposed via the cooperative‐competitive relationship between the agents. We demonstrate the group consensus with sufficient small errors can be achieved at time , as the number of iterations proceed to infinity. Then, the results are extended to the case of multisubgroups and multileaders. Finally, two simulations validate the findings of this article.","PeriodicalId":55453,"journal":{"name":"Asian Journal of Control","volume":"9 1","pages":""},"PeriodicalIF":2.4,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142186319","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}
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