Adaptive state feedback controller with Kalman filter observer for machining process

An adaptive state feedback controller (ASFC) with Kalman filter observer is presented for machining process control. The state equations of the process are derived from the second order transfer function. The analysis shows that the machining process is observable and controllable. The state variables are estimated by a Kalman filter observer. The objective of adaptive control for the machining process is given as a desired second order system and the adaptive controller is considered as a trace system with non-zero reference input. Then the adaptive control law is calculated by pole-assignment method in state space. The algorithms of the observer and controller are plugged into a real-time platform, intelligent machining module (IMM), as the plue-in-modules (PIMs) to build up the ASFC control system for off-line real time simulations and machining tests in the laboratory. The simulations and experiments under different cutting conditions demonstrate that the controller is stable, reliable and robust.