Design and Implementation of Interior-Point Method Based Linear Model Predictive Controller

  • Vihangkumar V. Naik
  • D. N. Sonawane
  • Deepak D. Ingole
  • Divyesh L. Ginoya
  • Neha S. Girme
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 296)


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.


Model Predictive Control Interior-Point Method LU factorization DC Servomotor 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Vihangkumar V. Naik
    • 1
  • D. N. Sonawane
    • 1
  • Deepak D. Ingole
    • 1
  • Divyesh L. Ginoya
    • 1
  • Neha S. Girme
    • 1
  1. 1.Department of Instrumentation & Control EngineeringCollege of EngineeringPuneIndia

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