LQR Predictive Control of SISO Time-Delay Processes Having Output Disturbances

This article details a new Model Predictive Control algorithm ensuring robust stability and control feasibility for uncertain nonlinear multi-input multi-output dynamical systems considering uncertain time-delay effects. The proposed control algorithm is based on construction of a Lyapunov–Krasovskii functional as terminal cost. Incorporation of this terminal cost into the Model Predictive Control optimization problem and calculation of the associated admissible set result in robust feasibility and robust stability of closed-loop system in presence of uncertain time-delay effects and bounded disturbance signals. The Lyapunov–Krasovskii functional term is constructed with respect to predicted sliding functions over the prediction horizon and considers the effects of dynamical variations over the prediction horizon in generation of control inputs. As dynamical variations are investigated in a sample-to-sample basis, feasible sliding regions are updated at each sample as well. Finally, based on expression of sliding functions as a combination of dynamical variations and input-based terms, required control inputs are calculated in the admissible bound by the optimization algorithm. Construction of control scheme on this basis permits straightforward calculation of robust stability and feasibility conditions for a general class of uncertain nonlinear system in finite prediction horizon whereas in the previous works, often-restrictive conditions were considered for the investigated dynamical systems. Numerical illustrations indicate precision and efficiency of control algorithm and improved stability and convergence rate for multivariable nonlinear dynamical systems considering uncertain time-delay effects. Finally, hardware-in-the-loop implementation indicates applicability of the proposed scheme in real-time control applications particularly in case appropriate compromises between optimality and calculation speed are considered.

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Explicit model predictive control of networked control systems with time-delay

2011 Chinese Control and Decision Conference (CCDC) ◽

10.1109/ccdc.2011.5968312 ◽

2011 ◽

Author(s):

Zhang Ju ◽

Zhang Haihua

Keyword(s):

Time Delay ◽

Model Predictive Control ◽

Control Systems ◽

Predictive Control ◽

Networked Control Systems ◽

Networked Control ◽

Explicit Model ◽

Explicit Model Predictive Control

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Nonfragile Robust Model Predictive Control for Uncertain Constrained Systems with Time-Delay Compensation

Mathematical Problems in Engineering ◽

10.1155/2016/1945964 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 1

Author(s):

Wei Jiang ◽

Hong-li Wang ◽

Jing-hui Lu ◽

Wei-wei Qin ◽

Guang-bin Cai

Keyword(s):

Time Delay ◽

Model Predictive Control ◽

Predictive Control ◽

Optimization Problems ◽

Sufficient Conditions ◽

Constrained Systems ◽

Delay Compensation ◽

Robust Model Predictive Control ◽

Robust Model ◽

Time Delay Compensation

This study investigates the problem of asymptotic stabilization for a class of discrete-time linear uncertain time-delayed systems with input constraints. Parametric uncertainty is assumed to be structured, and delay is assumed to be known. In Lyapunov stability theory framework, two synthesis schemes of designing nonfragile robust model predictive control (RMPC) with time-delay compensation are put forward, where the additive and the multiplicative gain perturbations are, respectively, considered. First, by designing appropriate Lyapunov-Krasovskii (L-K) functions, the robust performance index is defined as optimization problems that minimize upper bounds of infinite horizon cost function. Then, to guarantee closed-loop stability, the sufficient conditions for the existence of desired nonfragile RMPC are obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approaches.

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Predictive Control of a Laboratory Time Delay Process Experiment

Information Technologies and Control ◽

10.2478/itc-2013-0005 ◽

2013 ◽

Vol 11 (1) ◽

pp. 29-36

Author(s):

S. Enev

Keyword(s):

Time Delay ◽

Predictive Control ◽

Control Algorithm ◽

Optimization Problem ◽

Problem Formulation ◽

Practical Implementation ◽

Control Law ◽

Design And Implementation ◽

Optimization Problem Formulation ◽

Laboratory Time

Abstract The paper presents the design and implementation of a Model Predictive Control (MPC) scheme of a laboratory heatexchange process with a significant time delay in the input-output path. The optimization problem formulation is given and an MPC control algorithm is designed, achieving integral properties. Details, related to the practical implementation of the control law are discussed and the first experimental results are presented.

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