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Optimization of PI and Fuzzy-PI Controllers on Simulation Model of Szabad(ka)-II Walking Robot:

机译:Szabad(ka)-II步行机器人仿真模型中PI和Fuzzy-PI控制器的优化:

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The Szabad(ka)-II 18 DOF walking robot and its simulation model is suitable for research into hexapod walking algorithm and motion control. The complete dynamic model has already been built, and is used as a black box for walking optimization in this research. First, optimal straight line walking was chosen as our objective, since the robot mainly moves in this mode. This case can be tested and validated as well on the current version of our robot. An ellipse-based leg trajectory has been generated for this low-cost straight line walking. Currently a simple new Fuzzy-PI controller with three input variables is being constructed and compared with an previously used PI controller. The purpose of defining the rules and its optimization are to obtain a controller that provides walking with higher quality. Both the compared controllers have been optimized together with the parameters of the leg trajectory. The particle swarm optimization (PSO) method was chosen from several methods with our benchmark-based selection research and the help of specific test functions; moreover the previous research (the comparison of genetic algorithm (GA) and PSO) also led to this conclusion.
机译:Szabad(ka)-II 18自由度步行机器人及其仿真模型适用于六足步行算法和运动控制的研究。完整的动力学模型已经建立,并在本研究中用作步行优化的黑匣子。首先,选择最佳直线行走作为我们的目标,因为机器人主要以这种模式运动。这种情况也可以在我们的机器人的当前版本上进行测试和验证。对于这种低成本的直线行走,已经生成了基于椭圆的腿轨迹。当前,正在构建具有三个输入变量的简单的新型Fuzzy-PI控制器,并将其与以前使用的PI控制器进行比较。定义规则及其优化的目的是为了获得一种能够提供更高质量步行的控制器。被比较的两个控制器都已与腿部轨迹的参数一起进行了优化。通过基于基准的选择研究和特定测试功能,从多种方法中选择了粒子群优化(PSO)方法;此外,先前的研究(遗传算法(GA)和PSO的比较)也得出了这一结论。

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