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modelling of Chlorine Contact Tank and the Combined Applications of linear model predictive control and Computational Fluid Dynamics

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CHEMICAL PRODUCT AND PROCESS modelING 2009年第1期4卷

作者： Muslim, Abrar Li, Qin Tade, Moses O. Syiah Kuala Univ Aceh Indonesia Curtin Univ Technol Perth WA Australia

A dynamic model is developed to present chlorine decay in chlorine contact tank, and a single-input single-output (SISO) model that presents both chlorine dosing and decay process is developed in Simulink of Matlab software with considerations of the process disturbances of temperature and stagnant flow in the tank. A computational fluid dynamics (CFD) model of chlorine transport and decay in the tank is also developed with the use of mixture multiphase model to present the chlorine mixing and decay models in the tank. To optimally control free chlorine residual (FCR) concentration in the SISO system, a linear model predictive control (LMPC) is designed using the SISO system and LMPC control algorithm. The LMPC control objective is to regulate the optimal mass flow rates of gaseous chlorine to control the chlorine decay process inputs/outputs within the constraints. The results on the LMPC simulation using reference data from a real water plant show that the LMPC can control the FCR concentration in the tank within the constraint by regulating the optimal mass flow rates of gaseous chlorine. Commercial CFD software, FluentTM, has been used in this study to simulate the FCR distribution in the CCT channel based on the LMPC result.

关键词： chlorine contact tank free chlorine residual SISO model linear model predictive control computational fluid dynamics

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Encirclement of Moving Target Using linear model predictive control Via Feedback linearization

Encirclement of Moving Target Using Linear Model Predictive ...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： A. T. Hafez M. Iskandarani S. N. Givigi S. Yousefi Aboelmaged Noureldin A. Beaulieu Department of Electrical and Computer Engineering Queens University Royal Military College of Canada

ISBN: (纸本)9781479938414

A team of Unmanned Aerial Vehicles (UAVs) is used for the dynamic encirclement of a moving target in simulation. The encirclement tactic is defined for the situation in which a target is isolated and surrounded by a group of UAVs. It may be employed by a team of UAVs to neutralize the target and restrict its movement. A combination of decentralized linear model predictive control (LMPC) and Feedback linearization (FL) is implemented on the team of UAVs in order to accomplish dynamic encirclement around a moving target. The main contribution of this paper lays in the application of LMPC and FL to solve the problem of encirclement of a moving target using an autonomous team of UAVs in simulation.

关键词： linear model predictive control Unmanned Aerial Vehicles Feedback linearization Cooperative Robotics

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Wind Turbine Structural Load Reduction by linear Single model predictive control

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IEEE ACCESS 2020年 8卷 98395-98409页

作者： Barcena, Rafael Acosta, Tatiana Etxebarria, Ainhoa Kortabarria, Inigo Univ Basque Country UPV EHU Fac Engn Bilbao Elect Technol Dept Bilbao Spain Univ Fuerzas Armadas ESPE Dept Elect & Elect Sangolqui 1715231 Ecuador

A new model-based predictive controller (MPC), specially oriented to facilitate its practical implementation, is presented. This controller is devoted to reduce the structural load in the drive train or/and the rotor of a wind turbine. It keeps its complexity and computational load low, by using a single linear internal model throughout the full range of use. To validate the new approach, the performance of two versions of such a controller is compared to the baseline case. Specifically, the implemented controllers are focused on mitigating the torsional vibrations that appear in the drive-train during turbine operation for wind speeds above rated. First, numerical simulations are used to study the potential performance. Then, the proposed methodology is put into practice by using rapid prototypes of the real-time controllers applied to a specifically designed Hardware-in-the-Loop (HiL) simulator of wind turbines. This HiL simulator realistically reproduces the performance of the National Renewable Energy Laboratory (NREL) 5 MW wind turbine. In order to confirm the practical applicability of such MPC algorithms, the electronic platform mounted on the rapid-prototyping system has a similar -or inferior- computational power than the industrial control platforms used in the actual wind turbines. Anyway, the computational burden is analyzed in detail.

关键词： Wind turbines Rotors Load modeling Blades predictive models Aerodynamics Computational modeling Hardware-in-the-loop simulation linear model predictive control load reduction practical implementation parameter uncertainty real-time control wind turbine

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Using Multiple Quadrotor Aircraft and linear model predictive control for the Encirclement of a Target

Using Multiple Quadrotor Aircraft and Linear Model Predictiv...

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IEEE International Systems Conference

作者： Mohamad Iskandarani Ahmed T. Hafez Sidney N. Givigi Alain Beaulieu Camille Alain Rabbath Royal Military College of Canada Department of Electrical and Computer Engineering Queens University Department of Mechanical and Industrial Engineering Concordia University

ISBN: (纸本)9781467331074

A Multi-Unmanned Aerial Vehicle (UAV) team formed from two or more UAVs is used in the encirclement of a target. Encirclement is defined as the situation in which a target is isolated and surrounded by a UAV team in order to maintain awareness and containment of that target. In this paper, the problem of maintaining a circular path around a target is considered and a linear model predictive control (LMPC) strategy is implemented on a team of Qball-X4 quadrotor aircraft in order to follow the circular path. The linear plant controlled by the LMPC is a combination of process models found through system identification and a linear cartesian to polar transformation. A collision avoidance system, based on potential fields, is successfully implemented between the Qball-X4 quadrotors. The contribution of this paper lay in the application of LMPC to the problem of encirclement using a team of Qball-X4 quadrotors and the ability of these UAVs to apply a collision avoidance policy.

关键词： linear model predictive control Unmanned Aerial Vehicles Collision Avoidance

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Optimal prioritized infeasibility handling in model predictive control: Parametric preemptive multiobjective linear programming approach

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JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 2001年第2期109卷 385-413页

作者： Vada, J Slupphaug, O Johansen, TA Energos Trondheim Norway ABB Ind Oslo Norway Norwegian Univ Sci & Technol Dept Engn Cybernet N-7034 Trondheim Norway

All practical implementations of model-based predictive control (MPC) require a means to recover from infeasibility. We propose a strategy designed for linear state-space MPC with prioritized constraints. It relaxes optimally an infeasible MPC optimization problem into a feasible one by solving a single-objective linear program (LP) online in addition to the standard online MPC optimization problem at each sample. By optimal, it is meant that the violation of a lower prioritized constraint cannot be made less without increasing the violation of a higher prioritized constraint. The problem of computing optimal constraint violations is naturally formulated as a parametric preemptive multiobjective LP. By extending well-known results from parametric LP, the preemptive multiobjective LP is reformulated into an equivalent standard single-objective LP. An efficient algorithm for offline design of this LP is given, and the algorithm is illustrated on an example.

关键词： parametric programming preemptive programming infeasibility linear model predictive control

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Robust output tracking of constrained perturbed linear systems via model predictive sliding mode control

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INTERNATIONAL JOURNAL OF ROBUST AND NONlinear control 2020年第3期30卷 1258-1274页

作者： Steinberger, M. Castillo, I. Horn, M. Fridman, L. Graz Univ Technol Inst Automat & Control Inffeldgasse 21b A-8010 Graz Austria Univ Nacl Autonoma Mexico Fac Ingn Mexico City DF Mexico

A robustifying strategy for constrained linear multivariable systems is proposed. A combination of tracking model predictive control with output integral sliding mode techniques is used to completely reject bounded matched perturbations. It can be guaranteed that all constraints on inputs, states, and outputs are satisfied although only output information is used. Finally, real-world experiments with an unstable plant are presented in order to demonstrate the validity and the effectiveness of the proposed approach.

关键词： linear model predictive control output integral sliding mode output tracking sliding mode control

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A Comparative Study Between linear and Affine Multi-model in predictive control of a Nonlinear Dynamic System

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第6期15卷 1258-1263页

作者： Mezrigui, Houda Chagra, Wassila Ben Hariz, Maher Univ Tunis El Manar Natl Engn Sch Tunis LR11ES20 Anal Concept & Control Syst Lab Tunis 1002 Tunisia Preparatory Inst Engn Studies El Manar Tunis Tunisia

-model predictive control (MPC) is the most successful control strategy that coped in many areas. However, the success of an MPC scheme lies in the accuracy of the adopted prediction model. This paper treats the problem of MPC when there is a need to a larger domain of set-point values and best tracking performances. It presents a novel modeling structure for representing a nonlinear dynamic system based on its static nonlinear characteristic. Then, the Multiple Affine model (MAM) structure is compared to Multiple linear models (MLM) in a linear MPC (LMPC) scheme. It is noted that the MAM structure offers more precision for modeling and the much smaller number of models. Therefore, it guarantees the best tracking performances in terms of stability, speed and accuracy.

关键词： Affine models linear models static characteristic linear model predictive control prediction horizon tracking performances

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A novel nonlinear model predictive control design based on a hybrid particle swarm optimization-sequential quadratic programming algorithm: application to an evaporator system

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2016年第1期38卷 23-32页

作者： Rajabi, Farshad Rezaie, Behrooz Rahmani, Zahra Babol Univ Technol Fac Elect & Comp Engn Babol Sar Iran

This paper proposes a hybrid algorithm by combining particle swarm optimization (PSO) with sequential quadratic programming (SQP) to handle the optimization part of the nonlinear model predictive control (NMPC). In the proposed method, a nonlinear model of the plant is directly applied to predict the future behaviour of the system for a certain horizon. In each sampling time a constrained nonlinear optimization (CNO) problem has to be solved in order to find the optimizing input sequence with predefined length. These solutions minimize the errors between the predicted states and the desired ones of the system. Only the first optimizing input is applied to the system and the rest of the sequence is discarded. The whole prediction and optimization must be repeated for the next upcoming steps. The evolutionary and heuristic PSO algorithm in cooperation with the powerful local minimizing SQP algorithm can quickly find these optimizing solutions and also can satisfy the constrains. The evaporation process due to its nonlinear dynamics and the existence of disturbances affecting the evaporator is considered to evaluate the performance of the proposed method. The simulation results show that the controller designed via the proposed approach can make the system track the reference commands and satisfy the restrictions properly. Moreover, based on the simulation results it can be seen that this approach is more efficient in comparison with the NMPC method, in which only the SQP algorithm has been utilized for optimization, and also the linear model predictive control method.

关键词： linear model predictive control nonlinear model predictive control constrained nonlinear optimization particle swarm optimization sequential quadratic programming evaporator

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First-Order Methods in Embedded Nonlinear model predictive control

First-Order Methods in Embedded Nonlinear Model Predictive C...

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European control Conference (ECC)

作者： Kouzoupis, D. Ferreau, H. J. Peyrl, H. Diehl, M. Albert Ludwigs Univ Freiburg Fac Microsyst Engn Freiburg Germany ABB Corp Res Segelhofstr 1K CH-5405 Baden Switzerland

ISBN: (纸本)9783952426937

Several algorithms based on Nesterov's fast gradient method have been recently proposed in the literature for use in linear model predictive control (MPC). Their simple algorithmic schemes have attracted much attention for MPC applications on embedded hardware. The purpose of this paper is to investigate the suitability of these algorithms in a nonlinear MPC setup. We assess the necessary numerical modifications and analyze the additional online computational complexity. We illustrate our findings by combining different first-order methods with the real-time iteration (RTI) scheme for nonlinear MPC and using them to control a model of an inverted pendulum.

关键词： computational complexity embedded systems gradient methods iterative methods linear systems nonlinear control systems pendulums predictive control Nesterov fast gradient method RTI scheme embedded hardware embedded nonlinear model predictive control first-order methods inverted pendulum linear model predictive control nonlinear MPC setup numerical modifications real-time iteration scheme Computational modeling Convergence Gradient methods Heuristic algorithms linear programming Prediction algorithms

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model predictive control for ethanol steam reformers with membrane separation

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第4期42卷 1949-1961页

作者： Serra, Maria Ocampo-Martinez, Carlos Li, Mingming Llorca, Jordi Univ Politecn Cataluna Inst Robot & Informat Ind CSIC UPC Llorens & Artigas 4-6 E-08028 Barcelona Spain Univ Politecn Cataluna EEBE Inst Tecn Energet Barcelona Spain Univ Politecn Cataluna EEBE Ctr Res Nanoengn Barcelona Spain

This paper focuses on the dynamic modelling and the predictive control of an ethanol steam reformer (ESR) with Pd-Ag membrane separation stage for the generation of pure hydrogen. Hydrogen purity necessary to feed a proton exchange membrane fuel cell (PEMFC) is required. A non-linear dynamic model of the ESR is developed together with a procedure for adjusting the model parameters in order to fit a bank of experimental data of a real ESR system. Static and dynamic analysis of the non-linear ESR model is presented. From this non-linear model, a linear, reduced order and discretised model is derived and a model predictive controller (LMPC) is designed for the ESR system. control objectives are pure hydrogen flowrate tracking and ethanol inlet minimization. Comparisons between the non-linear and linear models are carried out to determine the control constraints. Finally, simulation results for the implemented LMPC controller are presented and discussed. (C) 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Ethanol steam reformer Staged-separation membrane reactor control-oriented model linear model predictive control

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