CONTROL SYSTEM DESIGN FOR AN AUTONOMOUS HELICOPTER USING PARTICLE SWARM OPTIMIZATION

This paper presents a control system design method for an autonomous helicopter using the Particle Swarm Optimization (PSO) method. In this paper, the nonlinear dynamic model of a miniature helicopter is directly used to design a control system without linearization process. The nonlinear dynamics of model helicopter is represented by sixteen state variables including flapping dynamics, engine dynamics, and rotor speed dynamics. PSO algorithm is adopted as an optimization solver. In the proposed method, controller gains are selected to minimize the error between the desired response and the actual response of helicopter control system. To improve the convergence speed, sequential quadratic programming (SQP) is integrated to the basic PSO algorithm. The performance of the designed control system for an autonomous helicopter is evaluated through fully nonlinear simulation.

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