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In this article, we present a method for tuning controller parameters for cascade PID based on the step response performance characteristics of a closed loop system with application to an unmanned aerial vehicle(UAV). With specifically designed system identification procedures, a neural network mapping is obtained automatically when the UAV is flying around the target height. With this network system model, a gradual regression and optimization algorithm is proposed to tune the controller. The regression model primly illustrated the relation between PID parameters with controller performance, and the construction for optimization cost function takes the physical significance of step response performance of flying machine into account. Experimental data collected from fight experiment when auto-tuner is implemented on a quadrotorcraft demonstrate the efficiency of the proposed method.

Auto-tuning for cascade PID height position controller of rotorcraft