Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking
WU Xing1, LOU Pei-huang1, YANG Lei2
1. Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China; 2. Jiangsu Miracle Logistics System Engineering Company Limited, Wuxi 214000, China
武星, 楼佩煌, 杨雷. 基于视野状态分析的机器人路径跟踪智能预测控制[J]. 机器人, 2009, 31(4): 357-364..
WU Xing, LOU Pei-huang, YANG Lei. Intelligent Predictive Control Based on State Analysis of Visual Field for Robot Path Tracking. ROBOT, 2009, 31(4): 357-364..
Abstract：An intelligent predictive control model based on state analysis of visual field is presented for path tracking of the automated guided vehicle(AGV) with vision navigation.An optimal conversion strategy of error states is used to replace the quadratic cost function and to describe the objective of predictive control,so difficulties in parameter selection of pure algebra optimizing methods can be avoided.A synchronous control approach is proposed to completely eliminate two path errors of the ideal rectification state and to keep an error-free tracking state eventually.For other states,an iterative algorithm with assumption-prediction-adjustment is used to realize a harmonious state conversion.Numerical simulations and tests demonstrate that a realizable speed difference output can always be generated to eliminate two path errors synchronously, quickly and smoothly at different error states and velocities.Furthermore,with its low computational complexity,the proposed algorithm can satisfy the demand from realtime processing of embedded control systems.
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