Design and Implementation of Interior-Point Method Based Linear Model Predictive Controller
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Linear model predictive control (MPC) assumes a linear system model, linear inequality constraints and a convex quadratic cost function. Thus, it can be formulated as a quadratic programming (QP) problem. Due to associated computational complexity of QP solving algorithms, its applicability is restricted to relatively slow dynamic systems. This paper presents an interior-point method (IPM) based QP solver for the solution of optimal control problem in MPC. We propose LU factorization to solve the system of linear equations efficiently at each iteration of IPM, which renders faster execution of MPC. The approach is demonstrated practically by applying MPC to QET DC Servomotor for position control application.
KeywordsModel Predictive Control Interior-Point Method LU factorization DC Servomotor
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