Control System Tuning For Unmanned Rotorcraft Using Particle Swarm Optimization Algorithm

Abstract

This paper presents an alternative approach to designing automatic flight control systems for unmanned rotorcraft using a Linear Quadratic Regulator (LQR) controller optimized via the Particle Swarm Optimization (PSO) algorithm. The research formulates control system design as a constrained optimization problem, where the cost function is defined as the sum of control errors over a finite simulation period, given a predefined desired flight trajectory. The proposed control system was developed for the ARCHER unmanned rotorcraft, designed at the Warsaw University of Technology. The tuning and optimization process was conducted using a linear vehicle model, enhanced with actuator saturation constraints to reflect flight control system limitations. The optimized weighting parameters were then tested on a fully nonlinear rotorcraft model developed in FLIGHTLAB software.