Thrust force control of drilling system using neural network

Thrust force and cutting torque are important outputs in the control of drilling systems. In this paper, a method for estimating and control the thrust force in the drilling process is proposed. First, a neural network model of thrust force is off-line constructed. Next, based on the neural modal of thrust force, a simulated neurocontroller is developed by using an online trained recursive least squares algorithm. Finally, the trained controller is applied to the drill machine to force the thrust force of the drilling system following the reference thrust force signal. The experimental results obtained demonstrate the effectiveness of the proposed method