Abstract
Mechatronic systems in the automotive applications are characterized by significant nonlinearities and tight performance specifications further exacerbated by state and input constraints. Model Predictive Control (MPC) in conjunction with hybrid modeling can be an attractive and systematic methodology to handle these challenging control problems. MPC is a systematic feedback control design technique that determines the control input via receding horizon optimal control. Its main appeal is in being able to enforce point wise-in-time constraints while providing the control designer with direct capability to shape the transient response by adjusting the weights in the objective function being minimized. MPC controllers can handle continuous-valued and discrete-valued control inputs; accommodate system parameter changes or subsystem faults, as long as they are reflected in the model used for on-line optimization.
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