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个人信息Personal Information

教授

博士生导师

硕士生导师

性别:男

毕业院校:哈尔滨工业大学

学位:博士

所在单位:机械工程学院

学科:车辆工程. 控制理论与控制工程. 机械电子工程

办公地点:大连理工大学机械工程学院知方楼8017

电子邮箱:yueming@dlut.edu.cn

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Constrained Adaptive Robust Trajectory Tracking for WIP Vehicles Using Model Predictive Control and Extended State Observer

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论文类型:期刊论文

发表时间:2018-05-01

发表刊物:IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

收录刊物:SCIE、EI

卷号:48

期号:5

页面范围:733-742

ISSN号:2168-2216

关键字:Adaptive robust control; extended state observer; input saturation; model predictive control (MPC); wheeled inverted pendulum (WIP) vehicle

摘要:This paper is concerned with a model predictive control (MPC) technique together with an adaptive robust scheme for the trajectory tracking of a wheeled inverted pendulum vehicle in the absence of platform velocity information, in addition to taking dynamic uncertainty and external disturbance into consideration. Specifically, to deal with velocity information loss and dynamic uncertainty, an extended state observer is introduced to evaluate the velocity vectors and model dynamics, where the uniformly ultimately bounded property of observer system can be guaranteed by using the Lyapunov stability theorem. With these observations, MPC is employed for the underactuated longitudinal subsystem to achieve longitudinal velocity tracking, as well as holding the pendulum-like vehicle body stability, and in particular taking the state and input saturation into account; at the same time, an adaptive robust controller is constructed for the rotational subsystem to realize the rotational velocity tracking, in which the adaptive laws can enhance the vehicle adaptability in diverse environment. In addition, a saturated trajectory generator with closed-loop characteristic is introduced so as to properly handle the velocity limitation and nonholonomic constraint simultaneously. The simulation results validate that the control system is robust against the external disturbance and model uncertainty, thereby demonstrating the effectiveness and robustness of the proposed control strategy.