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27th IEEE International Symposium on Industrial Electronics (ISIE)

作者： Lee, Junho Chang, Hyuk-Jun Kookmin Univ Dept Secured Smart Elect Vehicle Seoul South Korea Kookmin Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781538637050

In this paper, we analyze and verify explicit model predictive control (MPC) through the automated double-lane-change (DLC) maneuver by employing MATLAB/Simulink and CarSim. MPC has become a useful optimization method because it can anticipate future events of a system and fulfill constraints on states and inputs. However, the formidable computational complexities of online optimization are considered as a major drawback. Therefore, explicit MPC has been proposed and demonstrated to reduce the computational burden by treating the state vector as a parameter vector. This technique is referred to as multi-parametric quadratic programming (mp-QP). A DLC test of CarSim has been conducted to prove the efficacy of the proposed controller in an autonomous driving situation. In addition, a DLC test conducted using a driver model in CarSim, which is designed based on a MPC scheme, is presented for comparison with the proposed controller. The range of the prediction horizon is varied to explain the relation between the prediction horizon and the performance of the proposed controller;also, a variation of vehicle speed is implemented to prove the robustness of the proposed controller. The main contribution of this paper is to demonstrate the reduction of the computational loads of explicit MPC so that the MPC-based scheme can be designed using not only a 32-bit microcontrollers but also 16-bit, 8 bit- microcontrollers, or a field programmable gate array (FPGA), featuring relatively lower development costs and longer battery consistence.

关键词： Model predictive control explicit model predictive control multi-parametric quadratic programming double lane change constrained optimization

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A Softly Switching multiple Model Predictive Control for Aero-engines 6th

A Softly Switching Multiple Model Predictive Control for Aer...

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6th IFAC Conference on Engine Powertrain Control, Simulation and Modeling (E-COSM)

作者： Hao, Guang-Chao Zhang, Yong-Liang Wen, Si-Xin Du, Xian Yang, Bin Sun, Xi-Ming Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Beijing Power Machinery Inst Beijing 100074 CO Peoples R China Dalian Univ Technol Minist Educ Key Lab Intelligent Control & Optimizat Ind Equip Dalian 116024 CO Peoples R China

This paper presents a multiple model predictive control (MPC) with a softly switching for aero-engines. Firstly, the different local working regions of the nonlinear aeroengines model are linearized. Then, a model predictive controller is designed for each linear model. The traditional hard switching methods for multiple model predictive controllers may result in bad transient behavior. Therefore, a softly switching mechanism is studied in this paper, which adopts the convex combination of the MPC objective functions before and after switching to ensure the smooth transition of aero-engines when switching in adjacent regions. The multi-parametric quadratic programming (MP-QP) algorithm is then used to solve the suboptimal solution of the problem, which reduces the amount of calculation and obtains an explicit solution. Finally, the reported simulation results of the turbofan engine verify the effectiveness of the suggested algorithm. Copyright (C) 2021 The Authors.

关键词： Aero-engines control multiple model predictive control Softly switching multi-parametric quadratic programming

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Explicit MPC Solution Using Hasse Diagrams: Construction, Storage and Retrieval 27th

Explicit MPC Solution Using Hasse Diagrams: Construction, St...

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27th International Conference on Difference Equations and Applications (ICDEA)

作者： Mihai, Stefan S. Stoican, Florin Ciubotaru, Bogdan D. Natl Univ Sci & Technol Politehn Bucharest Dept Automat Control & Syst Engn 313 Splaiul IndependenteiSect 6 Bucharest 060042 Romania

ISBN: (纸本)9783031510519;9783031510496;9783031510489

This chapter provides new methods for the construction, storage and retrieval of the explicit MPC solution in the case with quadratic cost and linear constraints. By exploiting the geometric interpretation of the MPC problem, we: (i) construct the explicit solution (i.e., enumerate the critical regions and associated affine laws) in an efficient manner;(ii) store it as a partially ordered set;and (iii) provide a modified graph traversal algorithm for efficient point location (i.e., identifying the currently active critical region and its associated control law).

关键词： Explicit MPC Hasse diagram Point location problem multi-parametric quadratic programming

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Guaranteed Cost Control For Constrained Takagi-Sugeno Fuzzy Systems

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IFAC Proceedings Volumes 2009年第19期42卷 325-330页

作者： Carlos Ariño Emilio Pérez Antonio Sala Department of Industrial Systems Engineering and Design Universitat Jaume I Avenida Vicent Sos Baynat s/n. 12071 Castelló de la Plana Spain Dept. of Systems Engineering & Control at the Technical University of Valencia E-46022 Valencia Spain

Abstract This paper presents a novel control design technique in order to obtain a Guaranteed Cost Fuzzy Controller subject to constraints on the input channel. This Guaranteed cost control law is obtained via multi-parametric quadratic programming. The result is a piecewise fuzzy control law where the state partition is defined by fuzzy inequalities. The parameters of the Lyapunov function can be obtained previously using linear matrix inequalities optimization.

关键词： Takagi-Sugeno fuzzy control LMI quadratic stability parallel distributed compensation piecewise control multi-parametric quadratic programming Constrained Control

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A Softly Switching multiple Model Predictive Control for Aero-engines ⁎

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IFAC-PapersOnLine 2021年第10期54卷 477-482页

作者： Guang-Chao Hao Yong-Liang Zhang Si-Xin Wen Xian Du Bin Yang Xi-Ming Sun School of Control Science and Engineering Dalian University of Technology Dalian CO 116024 China Beijing Power Machinery Institute Beijing CO 100074 China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian CO 116024 China

This paper presents a multiple model predictive control (MPC) with a softly switching for aero-engines. Firstly, the different local working regions of the nonlinear aeroengines model are linearized. Then, a model predictive controller is designed for each linear model. The traditional hard switching methods for multiple model predictive controllers may result in bad transient behavior. Therefore, a softly switching mechanism is studied in this paper, which adopts the convex combination of the MPC objective functions before and after switching to ensure the smooth transition of aero-engines when switching in adjacent regions. The multi-parametric quadratic programming (MP-QP) algorithm is then used to solve the sub-optimal solution of the problem, which reduces the amount of calculation and obtains an explicit solution. Finally, the reported simulation results of the turbofan engine verify the effectiveness of the suggested algorithm.

关键词： Aero-engines control multiple model predictive control Softly switching multi-parametric quadratic programming

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Improving Reliability of Partition Computation in Explicit MPC with MPT Toolbox

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IFAC Proceedings Volumes 2011年第1期44卷 9260-9265页

作者： Samo Gerkšič Dept. of Systems and Control Jozef Stefan Institute Jamova 39 Ljubljana Slovenia

Abstract The paper addresses the problem of numerical issues and degeneracies in the parametric quadratic programming (pQP) algorithm, used for computing partitions of explicit model predictive controllers (eMPC) with the multi-parametric Toolbox (MPT). We summarise the pQP problem setup and the basic algorithm, analyse its implementation in MPT, expose the numerical issues and suggest a series of improvements for more reliable operation, which are relevant also for other pQP solvers.

关键词： explicit predictive control multi-parametric quadratic programming numerical methods

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A comparison of the computational efficiency of multi-parametric predictive control using generalised function parameterisations

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IFAC Proceedings Volumes 2012年第15期45卷 451-456页

作者： B. Khan J.A. Rossiter Automatic Control and Systems Eng. University of Sheffield UK

This paper considers the computational efficiency of using generalised function parameterisations for multi-parametric quadratic programming (mp-QP) solutions to MPC. Earlier work demonstrated the potential of Laguerre parameterisations for improving computational efficiency in that the parametric solutions either required fewer regions and/or gave larger volumes. This paper considers the potential of extending this concept to more general function parameterisations. Specifically the aim is to consider to what extent different function parameterisations affect the parametric solution complexity and feasible volumes. Extensive simulation results which suggest there are indeed benefits from using more general parameterisations than Laguerre.

关键词： Predictive control multi-parametric quadratic programming Feasibility Generalised function parametrisations

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Linear Machine: A Novel Approach to Point Location Problem

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IFAC Proceedings Volumes 2013年第32期46卷 445-450页

作者： Astha Airan Sharad Bhartiya Mani Bhushan Department of Chemical Engineering Indian Institute of Technology Bombay Mumbai India

In recent literature, explicit model predictive control (e-MPC) has been proposed to facilitate implementation of the popular model predictive control (MPC) approach to fast dynamical systems. e-MPC is based on multi-parametric programming. The key idea in e-MPC is to replace the online optimization problem in MPC by a point location problem. After locating the current point, the control law is simply computed as an appropriate linear function of the states. A variety of approaches have been proposed in literature for the point location problem. In this work, we present a novel approach based on linear machines for solving this problem. Linear machines are widely used in multi-category pattern classification literature for developing linear classifiers given representative data from various classes. The idea in linear machines is to associate a linear discriminant function with each class. A given point is then assigned to the class with the largest discriminant function value. In this work, we develop an approach for identifying such discriminant functions from the hyperplanes characterizing the given regions as in multi-parametric programming. Apart from being an elegant solution to the point location problem as required in e-MPC, the proposed approach also links two apparently diverse fields namely e-MPC and multi-category pattern classification. To illustrate the utility of the approach, it is implemented on a hypothetical example as well as on a quadruple tank benchmark system taken from literature.

关键词： explicit model predictive control linear machine classifier multi-parametric quadratic programming

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Explicit Model Predictive Control of Networked Control Systems with Packet Dropout

Explicit Model Predictive Control of Networked Control Syste...

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24th Chinese Control and Decision Conference (CCDC)

作者： Zhang Ju Qin Ting Zhang Haihua Zhejiang Univ Technol Coll Informat Engn Hangzhou 310032 Zhejiang Peoples R China

ISBN: (纸本)9781457720727

In order to estimate the packet dropout in Networked Control Systems (NCS), this paper presents an explicit model predictive control. We firstly transform the model for networked control systems with data packet dropout into piecewise affine form. Then we solve a constrained optimal control problem with PWA model. By using the method of explicit predictive control, which is based on multi-parametric quadratic programming method, we get a state feedback control law which is explicit to the states. Based on this control law, we show that the control law is piece-wise linear and continuous for the finite horizon problem. Thus, the on-line control computation reduces to the simple evaluation of a piecewise affine model. Since the algorithm does not require repeated line optimization, it improves the on-line calculation speed of the controller, making the system better real-time. The algorithm deals with the data packet dropout well. Simulation results show the effectiveness of the method.

关键词： network control system explicit model predictive control multi-parametric quadratic programming piecewise affine model

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On-line optimization via off-line parametric optimization tools

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COMPUTERS & CHEMICAL ENGINEERING 2000年第2-7期24卷 183-188页

作者： Pistikopoulos, EN Dua, V Bozinis, NA Bemporad, A Morari, M Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2BY England ETH Zentrum Automat Control Lab CH-8092 Zurich Switzerland

In this paper, on-line optimization problems with a quadratic performance criteria and linear constraints are formulated as multi-parametric quadratic programs, where the input and state variables, corresponding to a plant, are treated as optimization variables and parameters, respectively. The solution of such problems is given by (i) a complete set of profiles of all the optimal inputs to the plant as a function of state variables, and (ii) the regions in the space of state variables where these functions remain optimal. It is shown that these profiles are linear and the corresponding regions are described by linear inequalities. An algorithm for obtaining these profiles and corresponding regions of optimality is also presented. The key feature of the proposed approach is that the on-line optimization problem is solved off-line via parametric programming techniques, hence, at each time interval (i) no optimization solver is called on-line, (ii) simple function evaluations are required for obtaining the optimal inputs to the plant for the current state of the plant. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： real-time optimization model predictive control multi-parametric quadratic programming

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