Model-Free Predictive Control Using Polynomial Regressors

Model Predictive Control Using Polynomial Optimization

Model-free Predictive Control

Model predictive control, MPC, is a model-based control philosophy that select control actions by on-line optimization of objective functions. Design methods based on MPC have found wide acceptance in industrial process control applications, and have been thoroughly studied by the academia. Most of the work so far have relied on linear models of different sophistication because of their advanta...

Linear offset-free Model Predictive Control

This work addresses the problem of offset-free Model Predictive Control (MPC) when tracking an asymptotically constant reference. In the first part, compact and intuitive conditions for offset-free MPC control are introduced by using the arguments of the internal model principle. In the second part, we study the case where the number of measured variables is larger than the number of tracked va...

Robust Offset-free Model Predictive Control

In this paper a method for designing robust offset-free MPC controllers for (possibly) nonzero targets is presented. The proposed controller is guaranteed to track the controlled variable to its target for any plant that lies in a polytopic region. First, an off-line design of a robust unconstrained offset-free controller is accomplished, and a corresponding invariant region is computed in whic...

Robust Trajectory Free Model Predictive Control of Biped Robots with Adaptive Gait Length

This paper employs nonlinear disturbance observer (NDO) for robust trajectory-free Nonlinear Model Predictive Control (NMPC) of biped robots. The NDO is used to reject the additive disturbances caused by parameter uncertainties, unmodeled dynamics, joints friction, and external slow-varying forces acting on the biped robots. In contrary to the slow-varying disturbances, handling sudden pushing ...