针对港口重载自动导引运输车（AGV）工作中遇到的横向稳定问题，提出了一种基于三层控制结构的AGV在低附着系数路面下的横向稳定优化控制策略。其中上层控制器选用模型预测控制（MPC）算法，可对AGV动力学参数进行不断采样与预测并且可缓解与中、下层控制器串联带来的控制系统时间滞后问题。中层控制器利用遗传算法对模糊控制器进行参数寻优以应用于港口AGV车体稳定控制。下层控制器利用序列二次规划（SQP）算法将驱动转矩优化分配问题转化为二次规划子问题进行在线求解。搭建适用于港口AGV的Matlab/Simulink与Trucksim联合仿真平台，验证了本研究提出的策略的有效性与鲁棒性。

A horizontal stability optimization control strategy of port overload AGV under low attachment coefficient road surface was proposed based on three-layer control structure. The MPC algorithm was used in the upper controller, which can continuously sample and predict the AGV dynamic parameters and alleviate the time lag problem of the control system caused by the series connection with the middle and lower-level controllers. The genetic algorithm was used in middle-level controller to optimize the parameters of the fuzzy controller for application to the stable control of the port AGV body. The SQP algorithm was applied in the lower-level controller to convert the driving torque optimal distribution problem into a quadratic programming sub-problem  and find an online solution. The Matlab / Simulink and Trucksim joint simulation platform based on port AGV was constructed to verifies the validity and robustness of the proposed strategy.