{"title":"基于近似动态规划的非线性多智能体系统最优输出同步","authors":"H. Modares, F. Lewis, A. Davoudi","doi":"10.1109/IJCNN.2016.7727751","DOIUrl":null,"url":null,"abstract":"Optimal output synchronization of multi-agent leader-follower systems is considered. The agents are assumed heterogeneous so that the dynamics may be non-identical. An optimal control protocol is designed for each agent based on the leader state and the agent local state. A distributed observer is designed to provide the leader state for each agent. A model-free approximate dynamic programming algorithm is then developed to solve the optimal output synchronization problem online in real time. No knowledge of the agents' dynamics is required. The proposed approach does not require explicitly solving of the output regulator equations, though it implicitly solves them by imposing optimality. A simulation example verifies the suitability of the proposed approach.","PeriodicalId":109405,"journal":{"name":"2016 International Joint Conference on Neural Networks (IJCNN)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Optimal output synchronization of nonlinear multi-agent systems using approximate dynamic programming\",\"authors\":\"H. Modares, F. Lewis, A. Davoudi\",\"doi\":\"10.1109/IJCNN.2016.7727751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimal output synchronization of multi-agent leader-follower systems is considered. The agents are assumed heterogeneous so that the dynamics may be non-identical. An optimal control protocol is designed for each agent based on the leader state and the agent local state. A distributed observer is designed to provide the leader state for each agent. A model-free approximate dynamic programming algorithm is then developed to solve the optimal output synchronization problem online in real time. No knowledge of the agents' dynamics is required. The proposed approach does not require explicitly solving of the output regulator equations, though it implicitly solves them by imposing optimality. A simulation example verifies the suitability of the proposed approach.\",\"PeriodicalId\":109405,\"journal\":{\"name\":\"2016 International Joint Conference on Neural Networks (IJCNN)\",\"volume\":\"99 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Joint Conference on Neural Networks (IJCNN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2016.7727751\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Joint Conference on Neural Networks (IJCNN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2016.7727751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal output synchronization of nonlinear multi-agent systems using approximate dynamic programming
Optimal output synchronization of multi-agent leader-follower systems is considered. The agents are assumed heterogeneous so that the dynamics may be non-identical. An optimal control protocol is designed for each agent based on the leader state and the agent local state. A distributed observer is designed to provide the leader state for each agent. A model-free approximate dynamic programming algorithm is then developed to solve the optimal output synchronization problem online in real time. No knowledge of the agents' dynamics is required. The proposed approach does not require explicitly solving of the output regulator equations, though it implicitly solves them by imposing optimality. A simulation example verifies the suitability of the proposed approach.