{"title":"将粒子群算法应用于运动移动机器人在复杂动态环境下的PID控制","authors":"A. Aouf, L. Boussaid, A. Sakly","doi":"10.1109/ICEMIS.2017.8273012","DOIUrl":null,"url":null,"abstract":"In robot navigation problem, many variables should be controlled in order to obtain the best upshot at the end of task. Indeed, the mobile robot ought to avoid obstacles and reach its final destination with the nethermost time and the shortest trajectory. It should be stable, accurate and replies quickly. Motivated by these demands, Particle Swarm Optimization for optimal PID controller for motion planning in a real complex environment is developed. Comparing to a Fuzzy logic controller, simulation results shows the efficiency of our suggested method.","PeriodicalId":117908,"journal":{"name":"2017 International Conference on Engineering & MIS (ICEMIS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A PSO algorithm applied to a PID controller for motion mobile robot in a complex dynamic environment\",\"authors\":\"A. Aouf, L. Boussaid, A. Sakly\",\"doi\":\"10.1109/ICEMIS.2017.8273012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In robot navigation problem, many variables should be controlled in order to obtain the best upshot at the end of task. Indeed, the mobile robot ought to avoid obstacles and reach its final destination with the nethermost time and the shortest trajectory. It should be stable, accurate and replies quickly. Motivated by these demands, Particle Swarm Optimization for optimal PID controller for motion planning in a real complex environment is developed. Comparing to a Fuzzy logic controller, simulation results shows the efficiency of our suggested method.\",\"PeriodicalId\":117908,\"journal\":{\"name\":\"2017 International Conference on Engineering & MIS (ICEMIS)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Engineering & MIS (ICEMIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMIS.2017.8273012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Engineering & MIS (ICEMIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMIS.2017.8273012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A PSO algorithm applied to a PID controller for motion mobile robot in a complex dynamic environment
In robot navigation problem, many variables should be controlled in order to obtain the best upshot at the end of task. Indeed, the mobile robot ought to avoid obstacles and reach its final destination with the nethermost time and the shortest trajectory. It should be stable, accurate and replies quickly. Motivated by these demands, Particle Swarm Optimization for optimal PID controller for motion planning in a real complex environment is developed. Comparing to a Fuzzy logic controller, simulation results shows the efficiency of our suggested method.