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This paper investigates the gait stability control problem of the quadruped robot body. Due to the lack of action prediction in advance and effective adjustment of the motion state, it is difficult to enhance the body stability of the quadruped robot during its locomotion. A new control framework based on composite nonlinear feedback (CNF) is proposed, which is able to adjust the input torque of the system based on its current motion state. The controller consists of a model predictive control (MPC) and a nonlinear feedback part, which establishes a closed-loop system by state feedback. The error between the target state and the actual state is introduced to construct a nonlinear input compensation term, and the optimal input is solved, so as to form a composite nonlinear feedback control. The algorithm is also on the basis of the state estimation and the use of inertial measurement unit (IMU). The simulation results show that the performance on the body stability of the quadruped robot is improved and the robot appears adapt to more complex terrain during motion. The results illustrate the effectiveness of the proposed approach.
Xu et al. (Fri,) studied this question.