Kautz parametrization of the Model Predictive Control (MPC) method has shown its ability to reduce the number of decision variables in Linear Time Invariant (LTI) systems. This paper devotes to extend Kautz network to be used in MPC Algorithm for linear time-varying systems. It is shown that Kautz network enables us to maintain a satisfactory performance while the number of decision variables a...

In this brief, constrained multi variable model predictive control (MPC) strategy is investigated for a GE9001E gas turbine power plant. So the rotor speed and exhaust gas temperature are controlled manipulating the fuel command and compressor inlet guide vanes position. A nonlinear model is introduced using conventional mathematical models and ARX identification procedure as gas turbine plant ...

This paper considers fault-tolerant control (FTC) for constrained linear systems subject to partial actuator failures. An active fault-tolerant control scheme based on model predictive control (MPC) and fault detection and isolation (FDI) is proposed. The FDI module using a two-stage Kalman filtering algorithm provides simultaneous control parameter and state estimation, which are used to modif...

This paper presents an approximate multi-parametric quadratic programming approach to explicit solution of constrained linear MPC problems in the presence of bounded additive uncertainties, which is based on an orthogonal search tree structure of the state space partition. The explicit MPC controller minimizes the nominal value of the performance index and it is robust in the sense that all con...

Exact or approximate solutions to constrained linear model predictive control (MPC) problems can be precomputed off-line in an explicit form as a piecewise linear state feedback defined on a polyhedral partition of the state space. However, the complexity of the polyhedral partition often increases rapidly with the dimension of the state vector, and the number of constraints. Recently, several ...

In many cases economic optimal operation is the same as maximum plant throughput, which is the same as maximum flow through the bottleneck(s). This insight may greatly simplify implementation. In this paper, we consider the case where the bottlenecks may move, with parallel flows that give rise to multiple bottlenecks and with crossover flows as extra degrees of freedom. With the assumption tha...

This article presents a novel model predictive control (MPC) scheme that achieves input-to-state stabilization of constrained discontinuous nonlinear and hybrid systems. Input-tostate stability (ISS) is guaranteed when an optimal solution of the MPC optimization problem is attained. Special attention is paid to the effect that sub-optimal solutions have on ISS of the closed-loop system. This is...

A new inferential 2-step multiple input/multiple output (MIMO) model predictive control (MPC) of the particle size distribution (PSD) in emulsion polymerization processes is proposed. The bulk-like model describing the PSD is used with the material balances of initiator, radicals, monomer and surfactant. The inferential 2-step control strategy uses two measurements available online (without del...

A robust MPC for constrained discrete-time nonlinear systems with additive uncertainties is presented. The proposed controller is based on the concept of reachable sets, that is, the sets that contain the predicted evolution of the uncertain system for all possible uncertainties. If processes are nonlinear these sets are very difficult to compute. A conservative approximation based on interval ...

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