Random Search Optimization Approach for Human-Robot Systems Modeling

Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for studying many tasks of monotonous manual control, such as tracking a reference signal. The analysis of such a system forms the basis for understanding its stability and controllability features. It is necessary to know the parameters of the human operator model for studying and designing such a system, which may depend on the parameters of the plant. This paper proposes an approach to human operator parameters calculation in manual control systems based on derivative-free optimization method. For three coefficients of the PID controller, the parameters of the human operator model were calculated using the proposed algorithm in MATLAB/Simulink. The evolution of the system parameters in the process of searching for the extremum of the selected function is illustrated graphically. The proposed method can be applied as part of the robot's intelligent control in real-time.