Tuning of Nonlinear Model Predictive Controller for Parameter-Dependent Systems and its Application to the Speed Control of Spark Ignition Engines

  • Tahir Fatima
    Department of Electrical Engineering, Pakistan Institute of Engineering and Applied Sciences
  • Ohtsuka Toshiyuki
    Department of Systems Science, Graduate School of Informatics, Kyoto University

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  • <b>Tuning of Nonlinear Model Predictive Controller for Parameter-Dependent Systems and its Application to the Speed Control of Spark Ignition Engines</b>

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In this paper, we propose a systematic method for the efficient tuning of the performance index in Nonlinear Model Predictive Control (NMPC) of parameter-dependent systems. The quadratic cost function in NMPC is tuned by applying the inverse optimality conditions on the linear quadratic regulator designed for the linearized model using the Inverse Linear Quadratic (ILQ) regulator design method. This approach provides some tuning parameters that give a trade-offbetween the speed of the system’s response and the magnitude of the control input. We propose two systematic methods for the selection of parameter-dependent tuning parameter. This approach is applied to the speed control of mean-value model of Spark Ignition (SI) engines. Effectiveness of the proposed methods is elaborated in simulation results.

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