No abstract

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems of the structural instability basically, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control are based on fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system that is employed by only single algorithm because the system includes multiple nonlinearities. In this paper, a switching PID is considered for a control of saturation, and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between simulation and experiment. After that, the switching PID gains are determined using genetic algorithm for removing limit cycle by saturation. The control algorithm is applied by dual feedback concept based on disturbance observer. All the processes are investigated through simulations and are verified experimentally in a real humanoid system.