Abstract: A new MPC controller design and method that may be applied to various different types of model predictive control (MPC) controllers and methods for use in any desired or appropriate controller setting, such as for plants, and can be imposed on conventional predictive control schemes to provide tighter control when tracking complex setpoint trajectories. The method introduces a correction parameter ?, independent of plant gain, evaluated online at each control timestep to drive the plant output to its reference more accurately than the original schemes. In a linear system, the correction parameter converges to a constant when optimized (evaluated on-line). The new MPC controller and method can also be applied on a nonlinear system. In a non-linear system, where the time constant is non-linear, the correction parameter will be variable.

Abstract: A new MPC controller design and method that may be applied to various different types of model predictive control (MPC) controllers and methods for use in any desired or appropriate controller setting, such as for plants, and can be imposed on conventional predictive control schemes to provide tighter control when tracking complex setpoint trajectories. The method introduces a correction parameter ?, independent of plant gain, evaluated online at each control timestep to drive the plant output to its reference more accurately than the original schemes. In a linear system, the correction parameter converges to a constant when optimized (evaluated on-line). The new MPC controller and method can also be applied on a nonlinear system. In a non-linear system, where the time constant is non-linear, the correction parameter will be variable.