Model Predictive Control in Pulsed Electrochemical Machining

Abstract In this work a Model Predictive Control (MPC) approach is used for controlling a Pulsed Electrochemical Machining (PECM) process. The MPC problem is formulated in order to optimally reach a desired state while satisfying various restrictions. PECM is modeled as a constrained nonlinear system. In the first approach the system is input-output linearized and a linear MPC scheme is applied to control it. In comparison a second approach uses the linearization around the current working point resulting in a Linear Time Variant system. This linear system is controlled using Linear Time Variant MPC (LTV-MPC). The simulation results are compared and the most promising controller is implemented on a real time platform controlling a PECM plant. The experimental results with online parameter estimation are shown and discussed.

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