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Research on explicit model predictive control method for horizontal vibration of high-speed elevator car system

JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2025年第1期47卷 1-19页

作者： Zhang, Shengnan Zhang, Qing Su, Xiaolei Zhao, Zichun He, Qin Meng, Lingfei Shandong Jianzhu Univ Sch Mech & Elect Engn Jinan 250101 Shandong Peoples R China Shandong FUJIZY Elevator Co Ltd Dezhou 253400 Shandong Peoples R China

The high-speed elevator car frame system, as a multi-input multi-output system (MIMO), has the characteristics of multiple constraints, complex coupling relationships, and high dynamic adjustment requirements. In response to the above characteristics, this paper studies a horizontal vibration suppression strategy for a high-speed elevator car frame system based on explicit model predictive control. Firstly, considering the multifactor coupling phenomenon between the components, such as the car and the car frame, the dynamic equation of the semi-active control system for horizontal vibration of the car frame high-speed elevator was established. Secondly, an explicit model predictive control strategy (EMPC) for elevator semi-active systems is constructed by combining offline calculation of the optimal control law for elevator state feedback with online search, integrating multiple constraints in the car frame system into a quadratic programming problem for global optimization, effectively solving the control instability problem caused by multiple constraints in elevators. Fully considering the multivariable coupling relationship of high-speed elevators, joint optimization of multiple inputs in the elevator system is carried out based on multiparameter programming technology to minimize the control objective function. Establish an elevator state prediction model and call an offline state feedback control law to obtain the optimal control strategy that adapts to the new dynamics when the elevator system dynamically changes with load and external environment. Finally, the acceleration time-domain and frequency-domain responses of the semi-active control system for horizontal vibration of high-speed elevators under two operating conditions were analyzed through simulation calculations and compared with the numerical results under sliding mode control and traditional PID control. The performance of EMPC has significantly improved compared to passive suspension. Compared wi

关键词： Car frame system Horizontal vibration Multi-objective optimization explicit model predictive control Damping force adjustment

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Research on adaptive explicit distributed model predictive control strategy for horizontal vibration of high-speed elevator multi-agent car system

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2025年

作者： Zhang, Shengnan Zhang, Qing Su, Xiaolei Zhao, Zichun Wang, Yulei Shandong Jianzhu Univ Sch Mech & Elect Engn Jinan 250101 Shandong Peoples R China Shandong FUJIZY Elevator Co Ltd Dezhou Peoples R China

To solve the horizontal vibration problem of high-speed elevators caused by unevenness of guide rails and excitation of guide rail joints, considering the uncertainty of high-speed elevator parameters and multivariable coupling, an adaptive explicit distributed model predictive control strategy based on a multi-agent car system of high-speed elevators is proposed. First, the coupling constraints of high-speed elevator car are analyzed, and the horizontal vibration model of multi-agent car system is established. Second, the topology relationship of car multi-agent communication based on graph theory is analyzed, and the optimal control law of agent distribution model prediction is realized offline by multi-parameter programming technology. Meanwhile, by introducing a correction term with parameter estimation error, the uncertain parameter terms of the multi-agent car system can be estimated online. Design an adaptive explicit distributed model predictive control strategy for multi-agent car systems by combining offline collaborative distributed optimization with online uncertain parameter adaptive estimation. Finally, the time-domain and frequency-domain responses of high-speed elevator multi-agent car systems under two typical guide excitations are analyzed by simulation calculation and compared with the numerical results under passive control, adaptive control, and model predictive control. The results show that after the proposed control strategy is adopted, the mean horizontal vibration acceleration of the car system decreases by more than 48.4%, which further verifies the effectiveness of the proposed control strategy.

关键词： Multi-agent elevator car system horizontal vibration distributed optimization adaptive parameter estimation explicit model predictive control

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explicit model predictive control of Hybrid Systems and Multiparametric Mixed Integer Polynomial Programming

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AICHE JOURNAL 2016年第9期62卷 3441-3460页

作者： Charitopoulos, Vassilis M. Dua, Vivek UCL Ctr Proc Syst Engn Dept Chem Engn Torrington Pl London WC1E 7JE England

Hybrid systems are dynamical systems characterized by the simultaneous presence of discrete and continuous variables. model-based control of such systems is computationally demanding. To this effect, explicit controllers which provide control inputs as a set of functions of the state variables have been derived, using multiparametric programming mainly for the linear systems. Hybrid polynomial systems are considered resulting in a Mixed Integer Polynomial Programming problem. Treating the initial state of the system as a set of bounded parameters, the problem is reformulated as a multiparametric Mixed Integer Polynomial optimization (mp-MIPOPT) problem. A novel algorithm for mp-MIPOPT problems is proposed and the exact explicit control law for polynomial hybrid systems is computed. The key idea is the computation of the analytical solution of the optimality conditions while the binary variables are treated as relaxed parameters. Finally, using symbolic calculations exact nonconvex critical regions are computed. (C) 2016 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers

关键词： hybrid systems multiparametric programming mixed integer polynomial programming explicit model predictive control

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explicit model predictive control of DC-DC Switched-Mode Power Supplies With Extended Kalman Filtering

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2009年第6期56卷 1864-1874页

作者： Beccuti, Andrea Giovanni Mariethoz, Sebastien Cliquennois, Sebastien Wang, Shu Morari, Manfred ETH Automat Control Lab CH-8092 Zurich Switzerland ST Ericsson F-38019 Grenoble France

This paper presents a sensorless explicit model predictive control scheme for the dc-dc boost converter. No direct inductor current measurement is needed as the coil current is derived either via a static approximation or, for improved accuracy, through an extended Kalman filter. The estimate is used in the chosen optimal control problem formulation which yields the optimal input by intrinsically accounting for duty cycle and current constraints. The optimization problem is explicitly presolved offline so that the online effort is reduced to a simple search in the resulting lookup table. No online optimization is required, greatly facilitating physical implementation and allowing for experimental validation on an integrated dc-dc converter through a fixed-point DSP.

关键词： Boost converter dc-dc extended Kalman filter (EKF) explicit model predictive control model predictive control (MPC) switched-mode power supply (SMPS)

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explicit model predictive control of permanent magnet synchronous motors based on multi-point linearization

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2021年第12期43卷 2872-2881页

作者： Guo, Qian Pan, Tianhong Liu, Jinfeng Chen, Shan Jiangsu Univ Sch Elect & Informat Engn Zhenjiang Jiangsu Peoples R China Anhui Univ Sch Elect Engn & Automat 111 Jiulong Rd Hefei 230601 Anhui Peoples R China Univ Alberta Dept Chem & Mat Engn 9211 116 St Edmonton AB T6G 2V4 Canada

Permanent magnet synchronous motors (PMSMs) have been broadly applied in servo-drive applications. It is necessary to improve the performance of PMSM. An explicit controller designed for PMSM based on multi-point linearization is proposed to reduce the linearized model error caused by different running status of PMSM. The mathematical model of PMSM system in the synchronous rotating frame and the problem formulation are introduced at first. Then, the preliminaries about explicit model predictive control (MPC) algorithm are presented in this article. Based on this, the multi-point linearization model is created for explicit MPC controller design. Moreover, the block diagram of the proposed method for PMSM system is presented. Finally, the simulation results are provided to demonstrate that the proposed explicit MPC controller based on multi-point linearization achieves better performance than that based on traditional single-point linearization, but requires the same online computation time because of the offline optimization of explicit MPC.

关键词： Permanent magnet synchronous motors explicit model predictive control multi-point linearization

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explicit model predictive control with Gaussian Process Regression for Flows around a Cylinder

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IFAC-PapersOnLine 2018年第33期51卷 38-43页

作者： Sasaki, Yasuo Tsubakino, Daisuke Department of Aerospace Engineering Nagoya University Nagoya Japan

model predictive control (MPC) of a separated flow around a circular cylinder at a low Reynolds number is presented in this paper. In order to reduce online computational cost, we propose to extract an explicit control law from data obtained by a number of offline simulations of the closed-loop system under MPC. The Gaussian process regression is employed to extract a control law. The effectiveness of the obtained control law is verified by a numerical simulation. Although the control law uses information about the flow on the surface of the cylinder, flow separation and vortex shedding are successfully mitigated. Moreover, improvement of aerodynamic performances is also observed. © 2018

关键词： model predictive control Circular cylinders Closed loop systems control theory Flow control Flow separation Gaussian distribution Gaussian noise (electronic) Navier Stokes equations predictive control systems Regression analysis Reynolds number Vortex flow Vortex shedding Aero dynamic performance Computational costs explicit control law explicit model predictive control Gaussian process regression Low Reynolds number Off line simulations Separated flows

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explicit model predictive control design for artificial respiratory ventilation system

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INTERNATIONAL JOURNAL OF DYNAMICS AND control 2024年第6期12卷 1851-1859页

作者： Acharya, Debasis Pradhan, Subrat Kumar Das, Dushmanta Kumar Natl Inst Technol Nagaland Dept Elect & Elect Engn Dimapur 797103 India Indira Gandhi Inst Technol Dept Elect Engn Dhenkanal 759146 India

Artificial breathing support device is a medical emergency equipment. Such devices are directly associated with the body of a patient. Therefore, the control mechanism of such devices is a challenging task in terms of the comfort and safety of the patient during ventilation. In a pressure control ventilator (PCV), the air pressure developed by the ventilator must be synchronised with the desired air pressure of the patient under artificial ventilation. For the purpose of enhancing the pressure profile of the PCV system, an explicit model predictive control logic is designed. As EMPC avoids the iterative process, the computational burden can be minimised as compared to other traditional iterative control schemes. The performance of the proposed method is examined under different scenarios and compared with existing results.

关键词： explicit model predictive control Pressure control ventilator (PCV) Positive end-expiratory pressure (PEEP)

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explicit model predictive control via Nonlinear Piecewise Approximations

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IFAC-PapersOnLine 2016年第18期49卷 259-264页

作者： Trinh, Van-Vuong Alamir, Mazen Bonnay, Patrick Bonne, François CNRS GIPSA-lab Control Systems Department 11 rue des Mathématiques Saint Martin d'Hères38402 France Univ. Grenoble Alpes INAC-SBT CEA INAC-SBT GrenobleF-38000 France

In this paper, a novel identification methodology is proposed to capture general multivariate nonlinear relationships, with focus on the bounded-error approximation of model predictive control for constrained (non)linear systems. The formulation of the identification problem takes, at each iteration, the form of a constrained linear (or quadratic) optimization problem that is mathematically feasible as well as numerically tractable. The efficiency of the proposed method for the derivation of low-complexity explicit model predictive controllers is demonstrated via the constrained control of a thermodynamic power plant. © 2016

关键词： model predictive control Constrained optimization Identification (control systems) Iterative methods Linear systems Constrained controls explicit model predictive control explicit modeling Identification problem Non linear relationships Nonlinear approximation Numerically tractable Optimization problems

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explicit model predictive control via Nonlinear Piecewise Approximations

Explicit Model Predictive Control via Nonlinear Piecewise Ap...

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10th IFAC Symposium on Nonlinear control Systems (NOLCOS)

作者： Van-Vuong Trinh Alamir, Mazen Bonnay, Patrick Bonne, Francois CNRS GIPSA Lab Control Syst Dept 11 Rue Math F-38402 St Martin Dheres France Univ Grenoble Alpes INAC SBT F-38000 Grenoble France CEA Grenoble INAC SBT F-38000 Grenoble France

In this paper, a novel identification methology proposed to capture general multivariate nonlinear relationships, with focus on the bounded-error approximation of model predictive control for constrained (non)linear systems. The formulation of the identification problem takes, at each iteration, the form of a constrained linear (or quadratic) optimization problem that is mathematically feasible as well as numerically tractable. The efficiency of the proposed method for the derivation of low-complexity explicit model predictive controllers is demonstrated via the constrained control of a tlwrmodyicamic power plant. (C) 2016, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： System Identification Nonlinear Approximation explicit model predictive control

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explicit model predictive control and L₁-Navigation Strategies for Fixed-Wing UAV Path Tracking 22

Explicit Model Predictive Control and <i>L</i><sub>1</sub>-N...

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22nd Mediterranean Conference on control and Automation (MED)

作者： Oettershagen, Philipp Melzer, Amir Leutenegger, Stefan Alexis, Kostas Siegwart, Roland ETH Autonomous Syst Lab Tannenstr 3 CH-8092 Zurich Switzerland

ISBN: (纸本)9781479959013

A control strategy for fixed-wing Unmanned Aerial Vehicles is proposed and relies on the combination of linear model predictive control laws for the attitude dynamics of the system, along with an implementation of the L-1-navigation logic that provides attitude reference commands to achieve precise path tracking. The employed predictive controllers ensure the performance characteristics of the critical attitude loops, while respecting the actuation limitations of the platform along with safety considerations encoded as state constraints. Being explicitly computed, these strategies are computationally lightweight and allow for seamless integration on the onboard avionics. Once the desired attitude response characteristics are achieved, tuning the cascaded nonlinear L-1-navigation law becomes straightforward as lateral acceleration references can be precisely tracked. A wide set of experiments was conducted in order to evaluate the performance of the proposed strategies. As shown high quality tracking results are achieved.

关键词： attitude control autonomous aerial vehicles predictive control attitude dynamics cascaded nonlinear L1-navigation law explicit model predictive control fixed-wing UAV path tracking fixed-wing unmanned aerial vehicles lateral acceleration references linear model predictive control laws Acceleration Aerodynamics Aerospace electronics Mathematical model Vectors Vehicle dynamics Vehicles

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