Systems and methods for offset-free model predictive control

Techniques, systems and methods for designing, implementing, and operating model predictive controllers that can deliver perfect tracking of set points and that can reject the effect of disturbances when steady-state operation is reached are disclosed. High performance is achieved through the incorporation of set-point tracking costs, integral costs, and velocity costs, as well as the adoption of incremental model systems for prediction purposes. Embodiments can deliver offset-free performance for tracking set points with constant final values, set points of a ramp type, and set points of a parabolic form, while rejecting disturbances that have a constant final value. The approach reduces the complexity of model predictive control design, delivers improved performance, and requires modest computational power. An Incremental Model State Estimator (IMES) is disclosed that reduces the computation load required for producing estimated values for the unmeasured star vector of a model under the presence of unmeasured disturbances.