Modeling and Tracking Control of Unmanned Helicopter

In path tracking control systems of unmanned helicopters, it is essential to have high-performance controllers. Currently many design methods for tracking controllers have general control effects, but it is difficult to provide theoretical and practical basis for real unmanned helicopter tracking control systems. In this paper, the external PID controller of an unmanned helicopter is designed, in which an improved particle swarm optimization (PSO) algorithm is proposed to adjust controller parameters. To test and verify the performance of the controller, an improved artificial potential field (APF) method of tracking with combination of unmanned helicopter model. Firstly, safe distance of the unmanned helicopter is reserved in the course of flight. Secondly, the path planning produced by artificial potential field method is taken as the expected trajectory and the input into the unmanned helicopter model in real time to verify the control effect of the controller under complex and irregular conditions. Finally, the simulation is conducted to verify the feasibility of the proposed method and the rapidity of the responses. The simulation results show that the flight trajectory of the unmanned helicopter is basically consistent with the desired trajectory, and the tracking error trajectory has a high degree of convergence with reaching the target point smoothly.