Hybrid predictive control with intelligent optimization for a quadrotor helicopter

This paper presents a new hybrid intelligent solution for designing controller in the quadrotor helicopter system to stabilize the state variables in rder to efficiently track a desired reference trajectory. Control design and implementation in presence of the explicit nonlinear dynamics and the actuation constraints in the quadrotor system is a complex task. For this, a combination of linear model predictive control using the receding horizon strategy and an intelligent nonlinear model predictive control based on adifferential discrete particle swarm optimization method is proposed to overcome such difficulties. The main purpose of the proposed model predictive control scheme is to minimize the difference between predicted outputs and reference values, while there are some constraints on inputs and outputs in nonlinear quadrotor system. Simulation results demonstrate the efficiency of the proposed control scheme for a quadrotor system model.

Keywords:

Intelligent , Nonlinear Model Predictive Control , Receding Horizon , DDPSO , Optimization , Quadrotor