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This paper is focused on the problem of uncertain process control by using RMPC (robust model predictive control). A relevant class of RMPC algorithms is the one characterized by the use of the LMI framework. This field started in the middle of nineties and since then several works applying LMIs in the context of RMPC have been proposed. Most of them assume a polytopic representation of the process...
A robust model predictive controller is proposed for input constrained linear systems with discrete and distributed delay in the states, where uncertainty is described by an additive bounded disturbance. The method is an extension of recently developed, tube based model predictive control to time-delay systems. A robust local controller maintains the disturbed trajectory of the controlled system in...
An improved off-line robust model predictive control (MPC) is presented for a discrete time uncertain dynamic system with input constraints, where the uncertainties that satisfy the so-called norm-bound conditions exist in state matrices and input matrices. The new approach synthesizes the advantage of on-line MPC and off-line MPC. First, off-line, generate a sequence of asymptotically stable invariant...
This paper considers robust model predictive control for systems with polytopic uncertainty and bounded disturbance, where the system state is unmeasurable, and the model at the current sampling time is an exact combination of the vertices of the polytope. A parameter-dependent dynamic output feedback is used for this problem. At each sampling time, the optimization problems can be solved via LMI...
In this paper, a constrained robust model predictive control (MPC) is addressed for continuous-time systems with polytopic uncertainty. A modified fuzzy disturbance observer (MFDO) is applied to estimate the uncertainty at each vertex given by a linear model. The quantity of uncertainty estimated by the MFDO is utilized as a pseudo membership grade for each vertex. The state feedback MPC control law...
In this paper, we propose a model predictive control (MPC) law for a discrete time uncertain singular system with state delay and input constraints. The model uncertainty is assumed to be polytopic, and the delay is assumed to be unknown, but with a known upper bound. Using zero equation with the free variable matrix, we derive a sufficient condition for cost monotonicity in terms of LMI, which can...
Computationally efficient robust model predictive control algorithm applicable for linear systems with polytopic model uncertainty as well as bounded additive disturbances is explored. A form of control scheme consisting of a static state feedback and a dynamically evolving perturbation is used in such a way that the cost function can be minimized in a receding horizon fashion over a pre-determined...
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