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Learning based multi-obstacle avoidance of unmanned aerial vehicles with a novel reward 基于学习的无人飞行器多障碍规避与新型奖励
Complex Engineering Systems Pub Date : 2023-12-11 DOI: 10.20517/ces.2023.24
Haochen Gao, Bin Kong, Miao Yu, Jinna Li
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引用次数: 0
Multi-step policy evaluation for adaptive-critic-based tracking control towards nonlinear systems 基于自适应批判的非线性系统跟踪控制的多步策略评估
Complex Engineering Systems Pub Date : 2023-11-24 DOI: 10.20517/ces.2023.28
Xin Li, Jin Ren, Ding Wang
{"title":"Multi-step policy evaluation for adaptive-critic-based tracking control towards nonlinear systems","authors":"Xin Li, Jin Ren, Ding Wang","doi":"10.20517/ces.2023.28","DOIUrl":"https://doi.org/10.20517/ces.2023.28","url":null,"abstract":"Currently, there are a large number of tracking problems in the industry concerning nonlinear systems with unknown dynamics. In order to obtain the optimal control policy, a multi-step adaptive critic tracking control (MsACTC) algorithm is developed in this paper. By constructing a steady control law, the tracking problem is transformed into a regulation problem. The MsACTC algorithm has an adjustable convergence rate during the iterative process by incorporating a multi-step policy evaluation mechanism. The convergence proof of the algorithm is provided. In order to implement the algorithm, three neural networks are built, including the model network, the critic network, and the action network. Finally, two numerical simulation examples are given to verify the effectiveness of the algorithm. Simulation results show that the MsACTC algorithm has satisfactory performance in terms of the applicability, tracking accuracy, and convergence speed.","PeriodicalId":504274,"journal":{"name":"Complex Engineering Systems","volume":"103 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139241763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Reinforcement learning-based optimal adaptive fuzzy control for nonlinear multi-agent systems with prescribed performance 基于强化学习的具有规定性能的非线性多代理系统最佳自适应模糊控制
Complex Engineering Systems Pub Date : 2023-11-24 DOI: 10.20517/ces.2023.27
Hua Yue, Jianwei Xia
{"title":"Reinforcement learning-based optimal adaptive fuzzy control for nonlinear multi-agent systems with prescribed performance","authors":"Hua Yue, Jianwei Xia","doi":"10.20517/ces.2023.27","DOIUrl":"https://doi.org/10.20517/ces.2023.27","url":null,"abstract":"In this paper, the problem of optimal adaptive consensus tracking control for nonlinear multi-agent systems with prescribed performance is investigated. To address the issue of satisfying the initial value conditions in existing results, an improved performance function is employed as the prescribed performance boundary, effectively resolving this problem. Then, by employing the error transformation function, the constrained system is converted into an unconstrained one. Furthermore, fuzzy logic systems are employed to identify unknown system parts. By applying the dynamic surface technique, the problem of \"differential explosion\", which often occurs in backstepping, is solved. Moreover, a distributed optimal adaptive fuzzy control protocol based on the reinforcement learning actor-critic algorithm is proposed. Under the proposed control scheme, it is proved that all the signals within the closed-loop system are bounded, and the consensus tracking errors have remained within the predefined bounds. Finally, the numerical simulation results demonstrate the effectiveness of the proposed scheme.","PeriodicalId":504274,"journal":{"name":"Complex Engineering Systems","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139238776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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