Using inverse linear quadratic method for systematic tuning of performance index in nonlinear model predictive control

In this paper, we propose to use the inverse linear quadratic (ILQ) method for efficient tuning of performance index in nonlinear model predictive control (NMPC). First a linear quadratic regulator is designed for the linearized model using the ILQ approach and then inverse optimality conditions are used for tuning of quadratic weights in the performance index of NMPC. After that, NMPC algorithm is applied to the nonlinear model. This approach provides some free parameters which can be tuned for a trade-off between speed of the system´s response and magnitude of the control input.