This paper presents a new design of model predictive control which combines non‐minimal
state space (NMSS) and Laguerre functions. The utilization of NMSS omits the observer …

This paper examines the design of model predictive control using nonminimal state space
models, in which the state variables are chosen as the set of measured input and output …

In this paper, a novel model predictive control (MPC) formulation has been proposed to
solve tracking problems, considering a generalized offset cost function. Sufficient conditions …

This paper deals with the tracking problem for constrained nonlinear systems using a model
predictive control (MPC) law. MPC provides a control law suitable for regulating constrained …

This paper presents a tracking control scheme for nonlinear systems with input constraints
by combining the continuous-time model predictive control and the feedback linearization …

This paper considers Model Predictive Control (MPC) using a Non-Minimal State Space
(NMSS) form, in which the state vector consists only of directly measured system variables …

In this paper, we propose an extension to the existing Model Predictive Control scheme for
tracking. This extension is able to provide a solution for the case where the set of steady …

This article proposes a model predictive control scheme based on a non-minimal state-
space (NMSS) structure. Such a combination yields a continuous-time state-space model …

In this paper, we propose a novel method to solve the model predictive control (MPC)
problem for linear time‐invariant (LTI) systems with input and output constraints. We …

In this paper, the nonlinear robust reference tracking problem is considered and an
Improved Two‐Loop Nonlinear Model Predictive Control (ITL‐NMPC) design is proposed for …