Chattering reduction in sliding mode control of quadcopters using neural networks

Abstract

This paper is based on the attitude control of a quadcopter with external disturbances. Sliding mode control (SMC) is a robust control method suitable for control of quadcopter. But its robustness comes at the cost of high frequency switching called chattering. An Adaptive Neural Gain Scheduling Sliding Mode Control (ANGS-SMC) technique is proposed to solve the chattering problem. Control gain of SMC is adapted using feed forward neural network. Performance of the designed controller is compared by simulation in MATLAB.