Wheeled Mobile Robot Based on Adaptive Linear Quadratic Gaussian Control
文献类型：会议论文
| 作者 | Yubin Liao; Yongsheng Ou; Shan Meng |
| 出版日期 | 2017 |
| 会议地点 | 中国重庆 |
| 英文摘要 | To deal with the existing issues of input saturations and uncertain positioning corrupted by Gaussian noises in the tracking control of Wheeled Mobile Robot (WMR), this paper presents a framework which applies the Adaptive Linear Quadratic Gaussian (ALQG) control with Genetic Algorithm based on linear discrete system. The work of ALQG includes three aspects. First, to address the problem of input saturations, we consider a linear discrete system as the Lagrangian multiplier and saturation constraint as the inequality constraint, and the linear quadratic controller with the penalty function as the objective function is solved by the interior point method. Second, in the above implementation of Linear Quadratic Regulator control, the weighting matrix under different conditions may result in different tracking performances. To address this issue, weighting matrices of different initial poses and reference trajectories are adaptively explored by Genetic Algorithm with control performance indexes as constraint functions, and the optimal weighting matrix is final determined. Third, concerning the uncertainty problem in positioning, the Kalman Filter algorithm with real-time measurement of the disturbed position of the posture filter is applied in real time to obtain more accurate poses. The ALQG simulation of the WMR is carried out in the MATLAB software platform, and the tracking quality of the ALQG is discussed systematically. The results show that the trajectory tracking controller of wheeled mobile robot based on ALQG can track the target trajectory stably and has good anti-interference abilities. |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/11872]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2017 |
| 推荐引用方式 GB/T 7714 | Yubin Liao,Yongsheng Ou,Shan Meng. Wheeled Mobile Robot Based on Adaptive Linear Quadratic Gaussian Control[C]. 见:. 中国重庆. |
入库方式： OAI收割
来源：深圳先进技术研究院
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