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15th International Power Electronics and Motion control Conference and Exposition (EPE-PEMC ECCE Europe)

作者： Vlad, C. Rodriguez-Ayerbe, P. Godoy, E. Lefranc, P. Supelec E3S Automat Dept Gif Sur Yvette France Suplec Dept Energy Gif Sur Yvette France

ISBN: (纸本)9781467319720

This article proposes a model predictive control (MPC) design to control a fixed frequency DC-DC power converter in a defined operating domain. The prediction model used for the control synthesis is a piecewise affine approximation (PWA) that covers the whole operating range of the converter. Based on the obtained hybrid model a constrained optimal control problem is formulated and solved. The explicit form of the control law is derived offline as an affine state feedback controller. This explicit controller is stored in a look-up table for implementation. The experimental results show the potential advantages of this control approach in comparison with a static state-feedback or a classic PI controller.

关键词： explicit model predictive control hybrid systems Buck converter

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explicit model predictive control for Trajectory Tracking with Mobile Robots

Explicit Model Predictive Control for Trajectory Tracking wi...

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IEEE/ASME International Conference on Advanced Intelligent Mechatronics

作者： Maurovic, Ivan Baotic, Mato Petrovic, Ivan Univ Zagreb Fac Elect Engn & Comp Zagreb 41000 Croatia

ISBN: (纸本)9781457708398

In this paper the model predictive control (MPC) strategy is used to solve the mobile robot trajectory tracking problem, where controller must ensure that robot follows pre-calculated trajectory. The so-called explicit optimal controller design and implementation are described. The MPC solution is calculated off-line and expressed as a piecewise affine function of the current state of a mobile robot. A linearized kinematic model of a differential drive mobile robot is used for the controller design purpose. The optimal controller, which has a form of a look-up table, is tested in simulation and experimentally.

关键词： Mobile robots Optimization predictive models Robot kinematics Tracking Trajectory control system synthesis differential drive mobile robot explicit model predictive control explicit optimal controller design linearized robot kinematic model look-up table mobile robots piecewise affine function position control predictive control robot kinematics trajectory tracking

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explicit model predictive control of electromechanical coupling system

Explicit model predictive control of electromechanical coupl...

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Chinese Automation Congress (CAC)

作者： Cheng, Qi Ke, Ji Wang, Biao Ju, Yongfeng Hu, Doudou Chang An Univ Coll Elect & Control Engn Xian Shaanxi Peoples R China

ISBN: (纸本)9781728113128

Aiming at the control problem of electromech-anical systems with nonlinear, high sampling frequency and strong coupling characteristics, a control method based on explicit model prediction is proposed. Firstly, the mathematical model is established based on the three-phase asynchronous electromechanical coupling system. Then, the multi-parameter quadratic programming method is used to calculate the explicit optimal control rate of the AC motor system offline, and the control quantity corresponding to the current state is searched online. The experimental simulation results show that this strategy not only improves the running speed of the system but also solves the problem of excessive coupling of complex systems under the condition of ensuring stable and safe operation of the system.

关键词： Electromechanical coupling system Three-phase asynchronous motor explicit model predictive control Multi-parameter quadratic programming

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explicit model predictive control on the Air Path of Turbocharged Diesel Engines

Explicit Model Predictive Control on the Air Path of Turboch...

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American control Conference (ACC)

作者： Zhao, Dezong Liu, Cunjia Stobart, Richard Deng, Jiamei Winward, Edward Univ Loughborough Dept Aeronaut & Automot Engn Leicester Leics England

ISBN: (纸本)9781479901784

The turbocharged diesel engine is a typical multiinput multi-output (MIMO) system with strong couplings, actuator constraints, and fast dynamics. This paper addresses the air path regulation in turbocharged diesel engines using an explicit model predictive control (EMPC) approach, which allows tracking of the time-varying setpoint values generated by the supervisory level controller while satisfying the actuator constraints. The proposed EMPC framework consists of calibration, engine model identification, controller formulation, and state observer design. The proposed EMPC approach has a low computation requirement and is suitable for implementation in the engine control unit (ECU) on board. The experimental results on a turbocharged Cat (R) C6.6 diesel engine illustrate that the EMPC controller significantly improves the tracking performance of the exhaust emission variables against the decentralized single-input single-output (SISO) control method.

关键词： explicit model predictive control turbocharged diesel engines exhaust emissions regulation

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explicit model predictive control for a Cart Inverted Pendulum System 7

Explicit Model Predictive Control for a Cart Inverted Pendul...

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7th International Conference on Systems and control (ICSC)

作者： Elnaggar, Mahmoud Lasheen, Ahmed Cairo Univ Fac Engn Elect Power & Machines Dept Giza Egypt

ISBN: (纸本)9781538685372

This paper discusses the implementation of the explicit model predictive control for the inverted pendulum system. The proposed controller has three merits. First, it is able to produce the optimal control action with constraints satisfaction. Second, it reduces the online computational time by obtaining the offline solution of the optimization problem. Third, it ensures the overall system stability. The simulation results show that the proposed controller achieves an excellent performance.

关键词： model predictive control explicit model predictive control gap-metric concept and Inverted pendulum system

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explicit model predictive control of CSTR system based on PWA model 34

Explicit model predictive control of CSTR system based on PW...

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34th Chinese control Conference, CCC 2015

作者： Pu, Yang Yu-Hong, Wang College of Information and Control Engineering China University of Petroleum Qingdao China

ISBN: (纸本)9789881563897

Piecewise affine(PWA) system can be used to model non-linear and non-smooth processes accurately and describe characteristics of hybrid system excellently. explicit model predictive control is a control method which enables one to obtain an explicit control law for a range of interested operating conditions. In this paper, explicit model predictive control based on PWA model is investigated in depth. The proposed scheme is then applied to a continuous stirred tank reactor(CSTR) system. The simulation results show that the system achieves satisfactory control requirements and demonstrate the effectiveness of the proposed control method for the system. The paper provides a practical method to control the CSTR system. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： CSTR explicit model predictive control Hybrid System PWA model

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Using a Two-Level Structure to Manage the Point Location Problem in explicit model predictive control

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ASIAN JOURNAL OF control 2016年第3期18卷 1075-1086页

作者： Zhang, Ju Xiu, Xiaojie Xie, Zuozhang Hu, Biaobiao Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Zhejiang Peoples R China

The problem of determining the state region in which the current state point lies is referred to as the point location problem in the explicit model predictive control. In this paper, a two-level structure to store the state regions is proposed and two efficient methods for solving the point-location problem are developed;these are the two-level grid (TLG) method and the grid-BST method. The TLG method uses a tow-level hash table. Before building the two-level structure, the synonymy partitions are merged to reduce the memory storage demand. By setting each parameter in a triplet, the two-level hash table can reach its optimal state and balance the complexity among the memory storage, reprocessing (offline computation) and the online computation. The grid-BST method uses hash table as the first-level structure and builds the binary search tree in the hash grid in which there are many partitions. This two-level structure reduces reprocessing time significantly especially when the state partitions and the piecewise affine control laws (PWA control laws) are in a large number. Using the hyperplane (HP) as the node (not leaf node) of the tree, the method only stores all the different PWA control laws instead of the state partitions. The two proposed methods overcome the quick complexity growth when the number of polyhedral partitions increases and 2 numerical examples show the advantages of the proposed two methods.

关键词： Point location explicit model predictive control hash table binary search tree two-level grid grid-BST

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Intelligent explicit model predictive control based on machine learning for microbial desalination cells

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2019年第7期233卷 751-763页

作者： Wang, Jing Wang, Qilun Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing 100029 Peoples R China

Aiming at the online control problem of microbial fuel cells, this article presents a class of explicit model-predictive control methods based on the machine learning data model. The proposed method is divided into two stages: off-line design and on-line control. In the off-line design stage, (1) a feasible data set is collected by sampling the admissible state in the feasible region and solving the optimal model predictive control law for each sampling data point off-line, (2) a feasible sample discriminator is constructed based on the support vector machine-based binary classification in order to judge the whether the real sampling state is feasible, and (3) according to the feasible samples and the corresponding optimal control law, the control surface of explicit model predictive controller is constructed based on the machine learning methods. In the on-line control stage, the process data are collected in real time and the feasible control output is calculated by using the trained explicit predictive control surface. Extensive testing and comparison among the different machine learning algorithms, such as artificial neural network, extreme learning machine, Gaussian process regression, and relevance vector machine, are performed on the benchmark model of a class of microbial desalination fuel cells. These results demonstrate that the proposed explicit model predictive control method can avoid the exhausting optimization computing and is easy to realize on-line with good control performance.

关键词： Microbial desalination cells explicit model predictive control data-driven model machine learning

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Using hash tables to manage the time-storage complexity in a point location problem: Application to explicit model predictive control

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AUTOMATICA 2011年第3期47卷 571-577页

作者： Bayat, Farhad Johansen, Tor Arne Jalali, Ali Akbar Iran Univ Sci & Technol Dept Elect Engn Tehran *** Iran Norwegian Univ Sci & Technol Dept Engn Cybernet N-7491 Trondheim Norway

The online computational burden of linear model predictive control (MPC) can be moved offline by using multi-parametric programming, so-called explicit MPC. The solution to the explicit MPC problem is a piecewise affine (PWA) state feedback function defined over a polyhedral subdivision of the set of feasible states. The online evaluation of such a control law needs to determine the polyhedral region in which the current state lies. This procedure is called point location;its computational complexity is challenging, and determines the minimum possible sampling time of the system. A new flexible algorithm is proposed which enables the designer to trade off between time and storage complexities. Utilizing the concept of hash tables and the associated hash functions, the proposed method solves an aggregated point location problem that overcomes prohibitive complexity growth with the number of polyhedral regions, while the storage-processing trade-off can be optimized via scaling parameters. The flexibility and power of this approach is supported by several numerical examples. (c) 2011 Elsevier Ltd. All rights reserved.

关键词： Point location explicit model predictive control Computational complexity Data structures

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Design of explicit model predictive control for Constrained Linear Systems with Disturbances

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INTERNATIONAL JOURNAL OF control AUTOMATION AND SYSTEMS 2014年第2期12卷 294-301页

作者： Mohammadkhani, Mohammad Ali Bayat, Farhad Jalali, Ali Akbar Iran Univ Sci & Technol Dept Elect Engn Tehran Iran Univ Zanjan Dept Engn Fac Elect Engn Zanjan Iran

On-line model predictive control approaches require the online solution of an optimization problem. In contrast, the explicit model predictive control moves major part of computation offline. Therefore, eMPC enables one to implement a MPC in real time for wide range of fast systems. The eMPC approach requires the exact system model and results a piecewise affine control law defined on a polyhedral partition in the state space. As an important limitation, disturbances may reduce performance of the explicit model predictive control. This paper presents efficient approach for handling the problem of using eMPC for constrained systems with disturbances. It proposes an approach to improve performance of the closed loop system by designing a suitable state and disturbance estimator. Conditions for observability of the disturbances are considered and it is depicted that applying the disturbance's estimation leads to rejection of the response error. It is also shown that the proposed approach prevents the reduction of feasible space. Simulation results illustrate the advantages of this approach.

关键词： Disturbance observer explicit model predictive control multi-parametric programming robust model predictive control

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