自适应控制的非线性PID为基础的模拟神经网络的非完整移动式遥控装置

中文字数:3011,中文页数:6  英文字数:1614页数:7

Abstract
 An adaptive controller of nonlinear PID-based analog neural networks is developed for the velocity-and orientation-tracking control of a nonholonomic mobile robot. A superb mixture of a conventional PID controller and a neural network, which has powerful capability of continuously online learning, adaptation and tackling nonlinearity, brings us the novel nonlinear PID-based analog neural network controller. It is appropriate for a kind of plant with nonlinearity uncertainties and disturbances. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity-and orientation-tracking control of the nonholonomic mobile robot. The effectiveness of the proposed control algorithm is demonstrated through the simulation experiment, which shows its superior performance and disturbance rejection.

摘要:
 基于非线性PID类神经网络的自适应控制装置向着非完整性移动式遥控装置的速度和定向统调控制发展。将常见的PID控制器与神经网络组合，给我们带来新颖的基于非线性PID类神经网络的自适应控制装置，它具有超强的持续在线学习能力，适应能力，以及解决非线性故障的能力。它适用于非线性的不确定性扰动的装置。差异驱动非完整性移动式遥控装置的计算机模拟执行非完整性移动式遥控装置的速度和定向统调遥控。提出来的控制算法的有效性已通过模拟试验证实了其优越的性能和抗干扰性。

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自适应控制的非线性PID为基础的模拟神经网络的非完整移动式遥控装置相关论文