Optimized Balance Control for Bionic Kangaroo Robot During Stance Phase Using Hybrid Particle Swarm Optimization

In order to improve the control performance of bionic kangaroo robot during stance phase, an optimization method for balance control is studied in this paper. The bionic kangaroo robot is first simplified to an inverted pendulum model during stance phase, and a multi-rigid-body dynamics model of the robot is established using Lagrange method. A linear quadratic regulator for stance balance control is designed based on the dynamics model, in which the optimum weight matrix is obtained by hybrid particle swarm algorithm. Simulations are conducted on balance control of the robot during stance using the optimized LQR regulator. The settling time of the optimized balance control is shorter. Results show that the optimized control method can improve the control performance of the bionic robot with good robustness and rapidity.