LAUSR

The parameter tuning optimization design is realized for an active disturbance rejection controller (ADRC) in combination with the improvement of the existing swarm intelligence algorithm. Taking the optimization design and application of ADRC as an example, this paper is focused on investigating the improvement of the hybrid algorithm composed of fish swarm algorithm and particle swarm optimization algorithm and its application in parameter tuning of ADRC. The main contents are as follows. First, the parameters that need to be tuned are determined based on the composition and principle of the ADRC. The module building technology of S-function is adopted to create the module library of ARDC in terms of the modular construction idea and a complete simulation example of ADRC is built in Simulink. Second, the parameters are improved according to the proposed hybrid algorithm composed of the artificial fish swarm algorithm and the standard particle swarm optimization algorithm, and the control performance is tested by the MATLAB simulation of the ADRC whose parameters are optimized by using the algorithm. Finally, the flight attitude control of the unmanned aerial vehicle (UAV) is taken as an application example, and the fixed-wing UAV is selected as the research object. Through the analysis of the experimental results, the effectiveness of the optimized design is verified for the ADRC in the attitude control of the UAV.