Tuning of Performance Index in Nonlinear Model Predictive Control by the Inverse Linear Quadratic Regulator Design Method

摘要

This paper proposes the use of the inverse linear quadratic (ILQ) regulator design method for the efficient tuning of the performance index in nonlinear model predictive control (NMPC). First, a linear quadratic regulator is designed for the linearized model using the ILQ regulator design approach and then the inverse optimality conditions are applied to the designed regulator to tune the quadratic weights in the performance index of NMPC. After that, the NMPC algorithm is applied to the nonlinear model. This approach provides some tuning parameters that give a trade-off between the speed of the system's response and the magnitude of the control input. Moreover, this tuning methodology provides a free parameter that can be utilized to adjust the transient response as well as to obtain a balance between the magnitudes of the control inputs.