Application of stochastic optimal control to thin rib machining

The optimal control of stochastic systems, such as a thin rib machining process, can lead to improved productivity and enhanced accuracy. The paper addresses the problem of identification and optimal control of stochastic tool path error in a thin rib machining process, both analytically and experimentally. Tool path error, in numerically controlled machines, consists of both deterministic and stochastic components and is defined as the vector difference between the programmed path and the actual path taken by the tool relative to the workpiece. A methodology is developed to identify the cutting process parameters based on experimental data from the thin rib machining of microwave guides. An LQG optimal controller was designed to minimise the stochastic tool path error. The results of optimal controller simulation are discussed. The microprocessor- based online optimal controller was validated, on a small computer numerically controlled (CNC) milling machine, to demonstrate improved performance in the thin rib machining of microwave guides