Adaptive control of nonlinear PID-based analog neural networks for a nonholonomic mobile robot
Adaptive control of nonlinear PID-based analog neural networks for a nonholonomic mobile robot
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DOI：
10.1016/j.neucom.2007.04.014
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发表时间：
2008-03
期刊：
影响因子：
6
通讯作者：
Jun Ye
中科院分区：
文献类型：
--
作者：
Jun Ye
针对非完整移动的机器人的速度和姿态跟踪控制问题，提出了一种基于非线性PID的模拟神经网络自适应控制器。基于神经网络的非线性PID控制器是传统PID控制器与具有强大的在线学习、自适应和非线性处理能力的神经网络的完美结合。它适用于一类具有非线性、不确定性和干扰的对象。对差动驱动非完整移动的机器人的速度和姿态跟踪控制进行了计算机仿真。通过仿真实验验证了该控制算法的有效性，表明了其优越的上级性能和抗干扰能力。
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.