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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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Robust explicit model predictive control based on State Feedback Linearization for Buck Converter 9

Robust Explicit Model Predictive Control based on State Feed...

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IEEE 9th International Power Electronics and Motion control Conference (IPEMC-ECCE Asia)

作者： Chen, Jing Chen, Yu Tong, Lupeng Peng, Li Huazhong Univ Sci & Technol HUST State Key Lab Adv Electromagnet Engn & Technol Wuhan Hubei Peoples R China

ISBN: (纸本)9781728153018

explicit model predictive control (EMPC) regards the linear time-invariant model as the prerequisite to deduce the offline control laws for online control. Thus, EMPC cannot be directly applied to Buck converters with variable load. A tradeoff method is to linearize Buck model under a specific load to obtain the time-invariant model to perform EMPC. However, since the obtained offline control laws is derived under the specific load, its performance will be degraded when the load varies. To fix this problem, this paper proposes to utilize State Feedback Linearization (SFL) technology to transfer the variable load term from model parameter matrix to state variables and control parameter. Based on such an equivalent model, EMPC can be directly performed and load-independent offline control laws are obtained. With such a methodology, only the load-dependent state variables and control parameter need to be updated online to adapt load variation, and the obtained control laws need not to be changed and can be discretized into a look-up table to reduce online computational burden, which suits the high switching frequency scenarios well. Details of the proposed methodology are given in this paper. Simulation and experimental results are also provided to demonstrate the effectiveness of the proposed control methodology.

关键词： Buck converter explicit model predictive control State Feedback Linearization

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Design of explicit model predictive control for PMSM Drive Systems 29

Design of Explicit Model Predictive Control for PMSM Drive S...

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第29届中国控制与决策会议

作者： Shi Yuntao Xiang Xiang Zhang Yuan Zhu Hengjie Sun Dehui Key Laboratory of Beijing for Field-bus Technology & Automation North China University of Technology

ISBN: (纸本)9781509046584

The performance of current vector control for the permanent magnet synchronous motor(PMSM) is affected by factors such as cross-coupling,applying delay and parameter *** order to solve these problems,a current control strategy based on the model predictive control(MPC) algorithm is *** strategy uses the prediction state of MPC to reduce the effect of output delay on *** the advantages of MPC with multivariable system and system constraints,it can deal well with the current and voltage limitations in actual systems,and ensure the current tracking *** view of the heavy computational burden features of on-line MPC and it is difficult to meet real-time performance in motion control *** this paper,the explicit model predictive control(EMPC) is *** method solves the optimization problem through off-line multi-parameter quadratic programming(mp-QP).During real-time operation,it only needs to look up the table according to the current state to obtain the control law with affine form in the current optimization *** simulation results show that the method satisfies the system constraints and has good dynamic,static and anti-disturbance performance.

关键词： Permanent Magnet Synchronous Motor explicit model predictive control Multi-Parameter Programming

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Vertical stabilization of ITER plasma using explicit model predictive control

Vertical stabilization of ITER plasma using explicit model p...

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27th Symposium on Fusion Technology (SOFT)

作者： Gerksic, Samo de Tommasi, Gianmaria Jozef Stefan Inst Ljubljana Slovenia Univ Naples Federico II Assoc EURATOM ENEA CREATE I-80125 Naples Italy

In this work we explore advanced control algorithms for the vertical stabilization of plasma in the ITER tokamak for the case where a combination of ohmic in-vessel and superconducting poloidal actuators is used for effective response to disturbances subject to thermal constraints. We apply constrained linear-quadratic optimal control, which is a hybrid between conventional linear quadratic optimal control and model predictive control (MPC). We discuss the issues of practical implementation in the form of explicit MPC, which allows application to fast processes by avoiding the use of on-line optimization. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Tokamak control Vertical stabilization system Optimal control Constrained linear quadratic control explicit model predictive control

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Design of Attitude controller using explicit model predictive control for an Unmanned Quadrotor Helicopter

Design of Attitude Controller using Explicit Model Predictiv...

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Chinese Automation Congress (CAC)

作者： Li Jiajin Li Rui Shi Yingjing Zou Jianxiao Univ Elect Sci & Technol China Sch Automat Engn Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538635247

In this paper, an explicit model predictive control (EMPC) method is introduced for the design of attitude controller of an unmanned quadrotor helicopter. The explicit predictive control algorithm divides a long-term control problem into several short-term optimal control problems and still pursues the optimal solution to a certain extent. The traditional predictive control needs to be optimal online, so it needs complicated calculation. The explicit predictive control algorithm turns online control problems into offline control problems. We only need to find the corresponding control area in the online control, and the system can be controlled by simple calculation. Therefore, the algorithm is well suited for implementation on embedded systems. Simulation studies are carried out to verify the effectiveness of the algorithm.

关键词： unmanned quadrotor helicopter explicit model predictive control multi-parametric quadratic program attitude control optimal control

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Constrained explicit model predictive control with Load State Observer for PMSM Drive System 6

Constrained Explicit Model Predictive Control with Load Stat...

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6th IEEE International Conference on predictive control of Electrical Drives and Power Electronics (PRECEDE)

作者： Guo, Qian Pan, Tianhong Jiangsu Univ Sch Elect & Informat Engn Zhenjiang 212013 Jiangsu Peoples R China Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China

ISBN: (纸本)9781665425575

This paper provides a constrained explicit controller with load torque observer designed for PMSM drive system. model predictive control(MPC) depends heavily on the precision of the system model, thus, the load changes will affect its control performance. The aim of this article is to design a load state observer to reject the load disturbance and transfer the online optimization of MPC to offline so as to improve the performance of controller. The mathematical model of PMSM system in the synchronous rotating frame is described at first. Based on this, the load torque state observer is created for the explicit MPC controller. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are presented to clarify that the proposed explicit MPC controller with state observer achieves better performance than that without state observer.

关键词： Permanent magnet synchronous motors explicit model predictive control load state observer

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Accelerating explicit model predictive control by Constraint Sorting 21st

Accelerating Explicit Model Predictive Control by Constraint...

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Holaza, Juraj Oravec, Juraj Kvasnica, Michal Dyrska, Raphael Moennigmann, Martin Fikar, Miroslav Slovak Univ Technol Bratislava Inst Informat Engn Automat & Math Bratislava Slovakia Ruhr Univ Bochum Automat Control & Syst Theory Bochum Germany

explicit MPC represents one of the fastest ways of real-time MPC implementation. As the explicit MPC policy is optimization-free in real-time control, its efficiency is determined by solving a point location problem. This paper proposes the novel concept of accelerating explicit MPC that significantly speeds up the real-time evaluation of the point location problem. The introduced strategy has two layers: (i) an offline phase determines a smart order of the regions to be explored, and (ii) an online phase removes further regions to be explored on the fly based on the current value of the value function. The main advantage of layer (i) is that the order is evaluated offline, therefore, it does not increase the real-time implementation of explicit MPC. The implementation of layer (ii) slightly increases the real-time evaluation but leads to further speed-up of the point location problem. As the proposed layers are based just on the evaluation of some appropriate value function, the main benefit is that these layers are fully applicable also for higher-dimensional systems. Although the accelerated explicit MPC variant does not reduce the worst-case time of solving the point location problem, an extensive case study demonstrates the efficiency of the proposed strategy. Copyright (C) 2020 The Authors.

关键词： explicit model predictive control point location problem sequential search

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explicit model predictive control of Networked control Systems with Time-Delay

Explicit Model Predictive Control of Networked Control Syste...

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23rd Chinese control and Decision Conference

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

ISBN: (纸本)9781424487363

In order to deal with random communication time delay in Networked control Systems(NCS), an explicit model predictive control (eMPC) method is presented in this paper. The algorithm is based on multi-parametric quadratic programming to get a state feedback control law which is explicit to the states. And based on this control law, the piecewise affine model of the closed-loop model predictive control system is established. We show that the control law is piecewise 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 online optimization, it improves the on-line calculation speed of the controller, making the system better in real-time. The algorithm deals with the random communication time delay well. Simulation results show the effectiveness of the proposed method.

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

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Semi-explicit model predictive control of Quasi Linear Parameter Varying Systems

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EUROPEAN JOURNAL OF control 2023年 69卷

作者： Mate, Sammyak Jaju, Prakhar Bhartiya, Sharad Nataraj, P. S. V. Indian Inst Technol Syst & Control Engn Mumbai India Indian Inst Technol Dept Chem Engn Mumbai India

explicit linear model predictive control (MPC) is a proven method for constrained optimal control of fast, linear time invariant (LTI) dynamic systems. However, an extension to quasi-linear parameter varying (Q-LPV) systems requires overcoming significant challenges, since neither the explicit MPC law is piecewise linear in state nor are the critical regions polytopic. In this work, we propose a semi-explicit solution to a sub-optimal MPC solution for a class of Q-LPV systems, which are obtained as multiple linear model approximations to nonlinear systems. The sub-optimal MPC for Q-LPV systems, which has been shown to be stabilizing in an earlier work, requires an online solution of a quadratic program (QP). Casting the QP into a multiparametric form leads to a new class of multiparametric QP (mpQP), termed herein as generalized mpQP (GmpQP). Information about the critical regions and the MPC law are obtained offline using a semi-explicit solution of the GmpQP based on an implicit enumeration of the active sets. Three algorithms are compared for the online evaluation of the control law. Offline and online complexity of the proposed method are presented for an example, including comparison of computational speeds with well-known implicit QP solvers.(c) 2022 European control Association. Published by Elsevier Ltd. All rights reserved.

关键词： Q-LPV systems explicit model predictive control KKT conditions Region free approach

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An efficient nonlinear explicit model predictive control to regulate blood glucose in type-1 diabetic patient under parametric uncertainties

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BIOMEDICAL SIGNAL PROCESSING AND control 2022年第PartA期71卷 103166-103166页

作者： Acharya, Debasis Das, Dushmanta Kumar Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur India

With the aim of regulating plasma glucose level in a type-1 diabetic patient, a nonlinear explicit model predictive control (NEMPC) is developed. The computational complexity in analytical method due to iterative process can be avoided by NEMPC. The amplitude of control signal defines the exogenous insulin infusion rate. Therefore, it should be taken a special care such that physiological needs can be satisfied. The control signal is also minimized to avoid physical hazard due to oscillation. The cost of actuator is also minimized as small size actuator can care the control signal generated by the proposed method. Thus, a cost effective control scheme is suggested by using nonlinear EMPC to regulate blood glucose level in type-1 diabetic patient. Different types of cases with nominal parameters, uncertainties in parameter and disturbances, uncertainties in states of initial condition are examined using the proposed method. The robustness of the proposed control logic is also checked with control variability analysis. Different risk factor of hyperglycemia and hypoglycemia is also verified. The simulation results shows the effectiveness of proposed control scheme for regulating glucose concentration in type-1 diabetic patients. An improvement of settling the glucose level from hyperglycemia to basal level within 120 min avoiding chance of hypoglycemia shows the effectiveness of proposed method than existing one.

关键词： Blood glucose concentration Type 1 diabetes mellitus explicit model predictive control

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