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nonlinear model predictive control of PEMFC anode hydrogen circulation system based on dynamic coupling analysis

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2023年第6期48卷 2385-2400页

作者： Zhu, Yun Zou, Jianxiao Li, Shuai Peng, Chao Xie, Yucen Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China Univ Elect Sci & Technol China Shenzhen Inst Adv Study Shenzhen Peoples R China Swansea Univ Fac Sci & Engn Dept Mech Engn Swansea SA1 8EN Wales

Anode hydrogen circulation system with purge valve has become one of the most effective ways for proton exchange membrane fuel cell (PEMFC) to alleviate performance degrada-tion caused by nitrogen permeation and improve the hydrogen utilization rate. However, nonlinearity and multivariable coupling of the system make it difficult for PEMFC to ach-ieve pressure and hydrogen supply synchronous tracking under complex operating con-ditions. To solve the problem, a novel nonlinear model predictive control scheme based on coupling analysis is proposed in this paper. Firstly, coupling characteristics of the hydrogen circulation system and the control pairing of the multivariable system are analyzed based on the relative gain array method. Then a novel control scheme based on an adaptive model predictive controller and a nonlinear model predictive controller is designed to keep the anode pressure stable and sufficient hydrogen supply, which use nonlinear observers to estimate the internal states online. Finally, the proposed controllers are implemented in control experiments of a 50 kW PEMFC anode hydrogen circulation system. The results demonstrate that the proposed control approach has great dynamic performance, anti -disturbance ability and can maintain a high hydrogen utilization rate under purge opera-tion, current disturbance and uncertain intake pressure.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Proton exchange membrane fuel cell (PEMFC) Anode hydrogen circulation system Coupling analysis nonlinear model predictive control

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nonlinear model predictive control Approximation: Applications to Truck-Trailer control System 24

Nonlinear Model Predictive Control Approximation: Applicatio...

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24th International Conference on control, Automation and Systems

作者： Park, Suyong Nguyen, Duc Giap Jin, Yongsik Park, Jinrak Kim, Dohee Eo, Jeong Soo Han, Kyoungseok Hanyang Univ Dept Automot Engn Seoul 04763 South Korea Kyungpook Natl Univ Dept Mech Engn Daegu 41566 South Korea Elect & Telecommun Res Inst ETRI Robot IT Convergence Res Sect Daegu 42994 South Korea Hyundai Motor Co Dept Electrified Syst Control Res Lab Hwaseong 18280 South Korea

ISBN: (纸本)9798331517939;9788993215380

In this work, we demonstrate the effectiveness of nonlinear model predictive control (NMPC) approximation based on deep neural network (DNN). MPC has been widely adopted in autonomous driving control problems to handle multiple objectives and constraints. We first design the implicit NMPC for the forward and backward motions of a truck-trailer (TT) system, which follows the reference path while maintaining safety between the head truck (HT) and the trailer (TR). However, the computational load in implicit MPC makes it a challenge for real-time implementations. To alleviate the computational burden in implicit NMPC online, an NMPC approximation approach based on DNN is adopted in this study to achieve a parametric function approximation. We conduct a comparative study on the proposed approach and a baseline controller for control performance analysis, and the computational load is evaluated on a hardware-in-the-loop (HIL) experimental system.

关键词： Deep neural network truck-trailer system nonlinear model predictive control hardware-in-the-loop systems control policy approximation

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nonlinear model predictive control Based on Disturbance Observer for Cross-Domain Unmanned Platform 17th

Nonlinear Model Predictive Control Based on Disturbance Obse...

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17th International Conference on Intelligent Robotics and Applications

作者： Yan, Zefeng Xu, Denan Lu, Liang Yang, Junyu Han, Bin Huazhong Univ Sci & Technol Sch Mech Sci & Engn State Key Lab Intelligent Mfg Equipment & Technol Wuhan Peoples R China

ISBN: (纸本)9789819607976;9789819607983

To address the issue of trajectory tracking under dynamic wave disturbances, this study proposes a nonlinear model predictive control method based on disturbance observer (DO-NMPC). The disturbance observer performs online observation of the generalized disturbance forces encountered by the unmanned platform during its motion, estimating the loads caused by wave disturbances in real-time. This information is used for active compensation in the model predictive control algorithm, enabling the control system to actively suppress wave disturbances related to unmodeled dynamics that cannot be measured. Simulation tests were conducted to compare the performance of the proposed DO-NMPC control strategy with the LQR control strategy in tracking straight-line and rotational trajectories on the water surface under wave disturbances. The simulation results validate the robustness and advantages of the proposed control strategy.

关键词： Cross-domain unmanned platform Trajectory tracking nonlinear model predictive control Disturbance observer

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nonlinear model predictive control for Enhanced Navigation of Autonomous Surface Vessels 8

Nonlinear Model Predictive Control for Enhanced Navigation o...

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8th IFAC Conference on nonlinear model predictive control (NMPC)

作者： Menges, Daniel Tengesdal, Trym Rasheed, Adil Norwegian Univ Sci & Technol Dept Engn Cybernet Trondheim Norway SINTEF Digital Dept Math & Cybernet Trondheim Norway

This article proposes an approach for collision avoidance, path following, and antigrounding of autonomous surface vessels under consideration of environmental forces based on nonlinear model predictive control (NMPC). Artificial Potential Fields (APFs) set the foundation for the cost function of the optimal control problem in terms of collision avoidance and anti-grounding. Depending on the risk of a collision given by the resulting force of the APFs, the controller optimizes regarding an adapted heading and travel speed by additionally following a desired path. For this purpose, nonlinear vessel dynamics are used for the NMPC. To extend the situational awareness concerning environmental disturbances impacted by wind, waves, and sea currents, a nonlinear disturbance observer is coupled to the entire NMPC scheme, allowing for the correction of an incorrect vessel motion due to external forces. In addition, the most essential rules according to the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs) are considered. The results of the simulations show that the proposed framework can control an autonomous surface vessel under various challenging scenarios, including environmental disturbances, to avoid collisions and follow desired paths. Copyright (C) 2024 The Authors.

关键词： nonlinear model predictive control Artificial Potential Fields nonlinear Disturbance Observer Autonomous Surface Vessels Collision Avoidance Anti-Grounding

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nonlinear model predictive control for industrial robot arms based on feedforward compensation 43

Nonlinear model predictive control for industrial robot arms...

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43rd Chinese control Conference (CCC)

作者： Wu, Wei Xie, Mingyang Zhang, Min Wang, Congqing Nanjing Univ Aeronaut & Astronaut Nanjing 210000 Peoples R China

ISBN: (纸本)9798350366907;9789887581581

To address the problems of poor dynamic performance and tracking overshoot of existing control strategies for industrial robot arms, this paper proposed a feedforward compensation-based nonlinear model predictive control (FNMPC) framework to achieve better tracking performance. First, the nonlinear frictional force of a six-degree-of-freedom robot manipulator is obtained by utilizing the least squares parameter identification method, and a more accurate dynamic model of the manipulator is established via the Newton-Euler method. Second, an FNMPC strategy is designed to achieve accurate tracking control of the robot manipulator. Finally, the performance of the proposed FNMPC strategy is verified by conducting a semi-physical simulation comparison experiment. Semi-physical simulation results show that the proposed control strategy exhibits superior performance in terms of dynamic response stationarity and cumulative tracking error.

关键词： Manipulator dynamics Parameter identification nonlinear model predictive control Feedforward compensation Semi-physical simulation

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nonlinear model predictive control of Hydrocyclone Separation Efficiency 12

Nonlinear Model Predictive Control of Hydrocyclone Separatio...

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12th IFAC Symposium on Advanced control of Chemical Processes (ADCHEM)

作者： Jespersen, Stefan Hansen, Dennis Severin Bram, Mads Valentin Kashani, Mahsa Yang, Zhenyu Aalborg Univ AAU Energy Esbjerg Denmark

As oil fields mature, an increasing volume of water is produced alongside the oil and gas due to the injection of water to maintain reservoir pressure. The control of de-oiling hydrocyclones in produced water treatment on offshore oil and gas facilities is typically based on the pressure drop ratio (PDR). While PDR relates to the flow split in the hydrocyclone and affects the separation efficiency, it is only an indirect way to control the steady-state deoiling efficiency. When the separation facility is subjected to disturbances, e.g., changing inlet concentration or production volume, the separation efficiency changes dynamically. The PDR responds to changes in flow rate, but it cannot sense changes in inlet oil content. By deploying online oil-in-water monitors, the separation efficiency could, in principle, be measured and used for dynamic feedback. This work developed a plant model based on previously published models of PDR, separator water level, and hydrocyclone separation efficiency. A nonlinear model predictive controller is designed and placed in cascade with the existing PDR-based PI controller to optimize the hydrocyclone separation efficiency. The results indicate an increased separation efficiency and, thus, a potential reduction in discharged oil of approximately 12 percentage points. Copyright (c) 2024 The Authors.

关键词： De-oiling hydrocyclone separation efficiency nonlinear model predictive control produced water treatment

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nonlinear model predictive control for Mitigating Epidemic Spread using a Partial Differential Equation Based Compartmental Dynamic model 4

Nonlinear Model Predictive Control for Mitigating Epidemic S...

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4th modeling, Estimation, and control Conference (MECC)

作者： Street, Logan David, Deepak Antony Liu, Chunyan Ehrlich, Shelley Kumar, Manish Ramakrishnan, Subramanian Univ Cincinnati Dept Mech & Mat Engn Cincinnati OH 45221 USA Univ Cincinnati Div Biostat & Epidemiol Cincinnati Childrens Hosp Med Ctr Coll Med Cincinnati OH USA Univ Dayton Dept Mech & Aerosp Engn Dayton OH USA

We present a nonlinear model predictive control (NMPC) framework for epidemic spread mitigation using a Partial Differential Equation (PDE) based Susceptible-Latent-Infected-Recovered (SLIR) epidemiological dynamic model. The spatio-temporal epidemic spread predictions of the model were numerically validated in our previous work using empirical COVID-19 data for Hamilton County, Ohio, employing a single-objective Genetic Algorithm (GA) for training model parameters. The validated model serves as the basis for the NMPC prediction and control framework developed to support the design of optimal Non-Pharmaceutical Interventions for spread mitigation. We consider a cost function comprising the infection spread density and the cost of applied control, with the latter representing socioeconomic effects. With a prediction horizon (T-p) of 30 days and a control horizon (T-u) of 15 days. The NMPC investigates a uniformly distributed control scheme across the entire spatial domain for three different time periods of the COVID-19 pandemic with distinct infection trends. In summary, the article presents one of the first efforts towards developing an NMPC framework based on a spatio-temporal epidemic dynamic model. The results provide an analytical basis for improved spread mitigation of future epidemics. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： nonlinear model predictive control Partial Differential Equations Mathematical modeling Epidemic models Numerical Analysis Numerical Optimization

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nonlinear model predictive control for Enhanced Path Tracking and Autonomous Drifting Through Direct Yaw Moment control and Rear-Wheel-Steering 16th

Nonlinear Model Predictive Control for Enhanced Path Trackin...

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16th International Symposium on Advanced Vehicle control

作者： Tavo, Gaetano Stanol, Pietro Tavernini, Davide Montanaro, Umberto Tufo, Manuela Fiengo, Giovanni Perlo, Pietro Sorniotti, Aldo Univ Surrey Guildford GU2 7XH Surrey England Univ Sannio I-82100 Benevento Italy Kineton R&D I-80146 Naples Italy Interact Fully Elect VehicleS IFEVS I-10040 Turin Italy Politecn Torino I-10129 Turin Italy

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Path tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a nonlinear model predictive control (NMPC) approach that integrates multiple actuation methods, namely four-wheel-steering, longitudinal tyre force distribution, and direct yaw moment control, to execute drifting when this is beneficial for PT in emergency scenarios. Simulation results of challenging manoeuvres, based on an experimentally validated vehicle model, highlight the substantial PT performance improvements brought by: i) vehicle operation outside the envelope enforced by the current generation of stability controllers;and ii) the integrated control of multiple actuators.

关键词： active safety systems electrified vehicles modelling testing and validation autonomous drifting nonlinear model predictive control

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nonlinear model predictive control for trajectory tracking of quadrotors using Lyapunov techniques

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Science China(Information Sciences) 2022年第6期65卷 269-270页

作者： Dong WANG Quan PAN Jinwen HU Chunhui ZHAO School of Automation Northwestern Polytechnical University

Dear editor,In recent years, the research on trajectory tracking and collision avoidance control of quadrotor unmanned aerial vehicles(UAVs) has gained considerable attention [1, 2]. Since quadrotor UAVs are used exte... 详细信息

关键词： trajectory tracking obstacle avoidance input constraints commercial quadrotors nonlinear model predictive control

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nonlinear model predictive control Strategy for Limit Management of Aero-Engines

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INTERNATIONAL JOURNAL OF TURBO & JET-ENGINES 2022年第3期39卷 427-438页

作者： Du, Xian Ma, Yan-Hua Sun, Xi-Ming Dalian Univ Technol Sch Microelect 2 Linggong Rd Dalian 116024 Peoples R China Dalian Univ Technol Sch Control Sci & Engn 2 Linggong Rd Dalian 116024 Peoples R China

A Min-Max structure combined with several linear limit controllers are utilized for conventional aero-engines safety control, which is complex and conservative, therefore a new nonlinear model predictive control strategy is proposed that owns the ability to manage time-varying input/output limits during acceleration/deceleration transient states of aero-engines. Penalty function items are constructed according to the characteristics of input/output limits, and are incorporated in the cost function of online receding horizon optimization for limit management of aero-engines. Considering the large computational burden of nonlinear component-level aero-engine model directly used as prediction model, a piecewise linear model is built to describe the steady-state and dynamic properties of aero-engines and its design process is explained in detail. Further, computational efforts are investigated as control horizon, prediction horizon are varied in the improved nonlinear predictive controller. Particularly, when penalty function items are activated, control performance and computational burden are examined, thus providing guidelines for key parameters tuning. Simulations show two clear results. One is that computational efforts become larger for bigger control horizon or prediction horizon, but it depends more on control horizon than prediction horizon. The other is that the proposed method can handle time-varying input/output limits effectively without resulting in a great increase of computational burden.

关键词： aero-engine control nonlinear model predictive control limit management penalty function piecewise linear model computational efforts

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