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Observer-based distributed model predictive control of complex systems with state coupling constraints

IET control THEORY AND APPLICATIONS 2022年第13期16卷 1364-1372页

作者： Du, Shengli Cao, Boqi Li, Xu Beijing Univ Technol Sch Artificial Intelligence & Automat Beijing 100124 Peoples R China Minist Educ Engn Res Ctr Intelligent Percept & Autonomous Con Beijing Peoples R China Beijing Lab Smart Environm Protect Beijing Peoples R China Dalian Univ Technol Key Lab Precis & Non Tradit Machining Technol Min Dalian Peoples R China

In this paper, the cooperative distributed model predictive control (DMPC) problem of a class of complex systems consisting of several subsystems is studied. The states of these subsystems are coupled with each other, and thus bring challenges for the model predictive control algorithm. Moreover, though the subsystems can communicate with each other, they only can access to the output information of their neighboring subsystems. In this case, Luenberger observers are used to estimate the unknown states and a distributed prediction strategy is established for the studied system. Then, the optimal control of the closed-loop system is realized by designing distributed model predictive controller on the basis of the estimated states. The terminal constraints are introduced in the proposed DMPC algorithm to ensure the iterative feasibility and also the stability of the closed-loop. Finally, the effectiveness of the proposed method is verified by a numerical simulation.

关键词： distributed prediction strategy model predictive control algorithm large-scale systems DMPC algorithm observer-based distributed model predictive control state coupling constraints model predictive controller Luenberger observers complex systems distributed control neighboring subsystems cooperative distributed model predictive control problem predictive control unknown states observers optimal control closed-loop system

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Parallel Parking Path Planning and Tracking control Based on Simulated Annealing algorithm

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INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY 2024年第4期25卷 867-880页

作者： Yu, Leiyan Cai, Yongpeng Feng, Xiangbo Zhou, Yuanxue Hu, Zihua Tian, Meilan Sun, Shaohua China Univ Petr East China Sch Mech & Elect Engn Qingdao 266580 Peoples R China Weifang Airui Brake Syst Co Ltd Weifang 261057 Peoples R China

To address the issues of curvature discontinuity and terminal tire non-return in the parallel parking of autonomous vehicles, a novel parallel parking path planning method based on the combination of the quintic polynomial curve and an improved sigmoid function was proposed. First, a vehicle kinematic model was established. Second, considering the position, front wheel angle, and yaw angle constraints during the parking process, a hybrid superimposed curve was designed. The parking path planning problem was converted into an optimal control problem, with the maximum curvature and curvature at both ends as objective functions, and the parameters were optimized using the simulated annealing algorithm. Subsequently, for path tracking control, the simulated annealing algorithm was used to optimize the prediction time horizon of the model predictive control algorithm. Finally, a series of actual vehicle experiments were conducted based on the Apollo Autonomous Driving Developer Suite, and the effectiveness of the proposed path planning method was validated. Therefore, this method can provide a certain reference for automatic parking path planning technology.

关键词： Parallel parking Path planning Simulated annealing algorithm model predictive control algorithm Pure pursuit algorithm

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Subsonic and Transonic Mach Number Tracking control Strategy Design and Application in an Intermittent Wind Tunnel

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IEEE ACCESS 2025年 13卷 74592-74601页

作者： Ma, Liebo Yan, Cheng Xiong, Bo Wang, Liang China Aerodynam Res & Dev Ctr High Speed Inst Mianyang 621000 Peoples R China

In order to ensure the quality of test data, the Mach number control deviation should be kept within a given range during the continuous-traverse mode force measurement test in a wind tunnel. Currently, when establishing the continuous-traverse mode force measurement test technique in a one-meter-scale sub-transonic and supersonic wind tunnel, the maximum Mach number control deviation exceeds the given range (0.003) under the conditions of sub-transonic speed, large model blockage ratio and wide angle of attack range. This deviation fails to meet the test requirements. By analyzing the process of sub-transonic Mach number adjustment, it is found that the significant Mach number control deviation arises due to two main factors: first, the static pressure fluctuates substantially as a result of changes in the angle of attack;second, the choke finger fails to adjust accurately and eliminate these static pressure fluctuations in real time. To achieve Mach number control deviation less than 0.003, a Mach number tracking control strategy has been proposed, which is based on the choke finger model predictive control algorithm with feedforward-feedback structure and choke finger compensation algorithm. The proposed strategy has been successfully implemented in continuous-traverse mode force measurement test. The test results show that the Mach number control deviation remains within the given range of 0.003 by using Mach number tracking control strategy, and the strategy has good robustness under the condition that the model blockage ratio is less than 0.69%.

关键词： Wind tunnels Force measurement Inductors Fingers Prediction algorithms Aerodynamics predictive control PI control PD control Fluctuations Continuous-traverse mode force measurement test technique control deviation Mach number tracking control strategy model predictive control algorithm sub-transonic and supersonic wind tunnel

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Blood glucose regulation and control of insulin and glucagon infusion using single model predictive control for type 1 diabetes mellitus

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IET SYSTEMS BIOLOGY 2020年第3期14卷 133-146页

作者： Dias, Cifha Crecil Kamath, Surekha Vidyasagar, Sudha Manipal Acad Higher Educ Manipal Inst Technol Dept Instrumentat & Control Manipal India Manipal Acad Higher Educ Kasturba Med Coll Dept Med Manipal India

This study elaborates on the design of artificial pancreas using model predictive control algorithm for a comprehensive physiological model such as the Sorensen model, which regulates the blood glucose and can have a longer control time in normal glycaemic region. The main objective of the proposed algorithm is to eliminate the risk of hyper and hypoglycaemia and have a precise infusion of hormones: insulin and glucagon. A single model predictive controller is developed to control the bihormones, insulin, and glucagon for such a development unmeasured disturbance is considered for a random time. The simulation result for the proposed algorithm performed good regulation lowering the hypoglycaemia risk and maintaining the glucose level within the normal glycaemic range. To validate the performance of the tracking of output and setpoint, average tracking error is used and 4.4 mg/dl results are obtained while compared with standard value (14.3 mg/dl).

关键词： predictive control blood medical control systems sugar diseases artificial organs patient treatment physiological models biochemistry blood glucose longer control time insulin single model predictive controller glucagon infusion single model predictive control type 1 diabetes mellitus model predictive control algorithm comprehensive physiological model Sorensen model

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Research on static fault-tolerant control method of thruster based on MPC

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY 2021年第3期26卷 861-871页

作者： Ding, Xuelian Zhu, Daqi Yan, Mingzhong Shanghai Maritime Univ Shanghai Engn Res Ctr Intelligent Maritime Search Haigang Ave 1550 Shanghai 201306 Peoples R China

To ensure that the unmanned underwater vehicles (UUVs) can still successfully complete the corresponding tasks in the case of thrusters having faults, a novel fault-tolerant control strategy which combines the model predictive control (MPC) algorithm and the fault-tolerant reconstruction algorithm is presented in this paper. Firstly, a cascade control method based on model predictive control algorithm is introduced, and then the problem when the thrusters in the faulty condition are discussed. For different degrees of thruster fault, the method of weighted pseudo inverse and quantum particle swarm optimization (QPSO) is used for hybrid fault-tolerant control (FTC). At the same time, to overcome the limitations brought by the pseudo inverse reconstruction algorithm, an optimization criterion with the infinite norm as the cost function is introduced into the QPSO algorithm to accelerate the search for the optimal solution in the feasibility space so as to ensure the feasibility of the solution. The simulation results show that the fault-tolerant control method proposed based on MPC (FTC-MPC) in this paper can provide ideal control effects for the unmanned underwater vehicles.

关键词： model predictive control algorithm Fault-tolerant reconstruction Weighted pseudo inverse Quantum particle swarm optimization algorithm Unmanned underwater vehicles

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Non-local harmonic current and reactive power compensation for a multi-microgrid system using a series-shunt network device

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第23期14卷 5655-5666页

作者： John, Thomas Patsios, Charalampos Greenwood, David Newcastle Univ Sch Engn Newcastle Upon Tyne NE1 7RU Tyne & Wear England

In this study, a new non-local active compensation method is developed for a multi-microgrid (MMG) system. The current industry practice is to utilise local harmonic current and reactive power compensation methods, however, local compensation methods are not practical for large MMG system with widely dispersed non-linear loads, because each non-linear load would require its own compensator. To overcome this problem, a novel compensating technology called a series-shunt network device (SSND) is installed between a pair of microgrids in the proposed MMG system. The SSND reduces the number of local compensators required while also performing additional functions in comparison with conventional devices. For effective control of the SSND, an improved model predictive control (MPC) algorithm, which gives better tracking accuracy and faster set-point change than that of a conventional proportional-integral controller, is also presented. Analysis and simulations verify the capability of SSND in performing both local and non-local active compensation of harmonic current and reactive power in the proposed MMG system under various test scenarios. Simulation results show that the MPC-controlled SSND can achieve effective compensation, thereby resulting in a very low current total harmonic distortion value of 2.4% and a unity power factor at the distribution grid side.

关键词： harmonic distortion PI control power factor compensation distributed power generation reactive power control predictive control power system harmonics power generation control power distribution control multimicrogrid system series-shunt network device nonlocal active compensation method current industry practice reactive power compensation MMG system nonlinear load model predictive control algorithm proportional-integral controller MPC-controlled SSND total harmonic distortion compensating technology nonlocal harmonic current local harmonic current power compensation SSND control unity power factor distribution grid side

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Path planning of autonomous agricultural machineries in complex rural road

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JOURNAL OF ENGINEERING-JOE 2020年第6期2020卷 239-245页

作者： Cui, Jinbo Zhang, Xianfeng Fan, Xinmiao Feng, Wei Li, Ping Wu, Yu Chongqing Acad Agr Sci Chongqing Peoples R China Sichuan Normal Univ Coll Movie & Media Chengdu Peoples R China

This study mainly investigates the path planning and collision avoidance problem of autonomous agricultural machineries in the complex rural road. First, the grid model is used to build the global map of machineries and the particle swarm optimisation algorithm is used to search the global path. A non-linear dynamic inertia weight is introduced to avoid the local lock-up problem of traditional particle swarm optimisation. Then the artificial potential energy method for addressing the local collision problem is used, which is the sum of the attraction of the target point and the repulsion of the obstacles and the road boundary force. To solve the problem of the slip and roll of autonomous machinery caused by complex roads, a machinery dynamic model considering road curvature and topographic inclination is established, and the model predictive control algorithm is used to track the planned path. The simulation results show that proposed method can make the autonomous agricultural machinery driving safely and smoothly.

关键词： predictive control collision avoidance particle swarm optimisation agricultural machinery nonlinear dynamic inertia weight traditional particle swarm optimisation road boundary force autonomous machinery model predictive control algorithm autonomous agricultural machinery path planning collision avoidance problem particle swarm optimisation algorithm machinery dynamic model

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Coordinated control for path following of two-wheel independently actuated autonomous ground vehicle

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IET INTELLIGENT TRANSPORT SYSTEMS 2019年第4期13卷 628-635页

作者： Tang, Zhao Xu, Xing Wang, Feng Jiang, Xinwei Jiang, Haobin Jiangsu Univ Sch Automot & Traff Engn Zhenjiang Jiangsu Peoples R China Jiangsu Univ Automot Engn Res Inst Zhenjiang Jiangsu Peoples R China

This study investigates the path following control problem about distributed-drive self-driving vehicle through coordinated control of the autonomous front-wheel steering and the differential steering control, to improve the tracking performance. On the basis of the model predictive control algorithm and vehicle dynamic model, the preview time adaptive control of path following is proposed to realise path following with changing preview time in straight and turning conditions. Considering the characteristics of the distributed-drive self-driving vehicle, the differential torque control is utilised based on the reference heading angle to realise trajectory tracking under the condition of constant torque demands. To integrate the advantages of the two methods, coordinated control of trajectory tracking based on the autonomous steering and differential steering is performed by setting the weight coefficients method. MATLAB co-simulation with Carsim and road testing validation are executed, and both demonstrate that the coordinated control strategy can not only effectively improve the response speed and flexibility of steering, but also improve the reliability and accuracy of trajectory tracking.

关键词： steering systems electric vehicles wheels road vehicles mobile robots torque control position control adaptive control predictive control vehicle dynamics control system synthesis model predictive control algorithm preview time adaptive control self-driving vehicle differential torque control trajectory tracking autonomous steering coordinated control strategy autonomous ground vehicle control problem front-wheel steering differential steering control tracking performance

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Power quality enhancement by MPC based multi-level control employed with improved particle Swarm optimized selective harmonic elimination

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ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 2019年第19期41卷 2396-2414页

作者： Reddy, N. Narender Chandrashekar, Obbu Srujana, A. Koneru Lakshmaiah Educ Fdn Guntur 522502 Andhra Pradesh India Sri Venkateswara Engn Coll Dept EEE Suryapet Telangana India

In the past decades, the number of distributed generators (DG) which are sensitive to adverse environments, the disturbances introduced by the nonlinear load and proliferation of renewable energy sources are increased considerably. This fetches the importance of power quality improvement. Also the sudden changes in the operating conditions of DGs due to load disturbances and network contingencies produce harmonics. In order to overcome the above issues in this research work, we proposed to design a novel model predictive control algorithm based Tree structured multi-level control system. The utilization of Extended Kalman filter with MPC expresses the harmonic signatures produced in the system which can be used to detect islanding. An Improved Particle Swarm Optimized Selective harmonic Elimination is finally employed to reduce the harmonics which significantly improves the quality of power delivered to the load. Our proposed control system has been implemented in the working platform of MATLAB/SIMULINK and tested with certain load conditions. The simulation results of the proposed control system and comparison with existing control systems show the significance of the proposed work.

关键词： Microgrids multilevel control system model predictive control algorithm Extended Kalman Filter (EKF) islanding Improved Particle Swarm Optimization (IPSO) Selective Harmonic Elimination (SHE)

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Laser-based SLAM automatic parallel parking path planning and tracking for passenger vehicle

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IET INTELLIGENT TRANSPORT SYSTEMS 2019年第10期13卷 1557-1568页

作者： Song, Jie Zhang, Weiwei Wu, Xuncheng Cao, Haotian Gao, Qiaoming Luo, Suyun Shanghai Univ Engn Sci Coll Mech & Automot Engn Shanghai 201620 Peoples R China Hunan Univ State Key Lab Adv Design & Mfg Vehicle Body Changsha 410082 Hunan Peoples R China Guangxi Univ Sci & Technol Coll Automobile & Transportat Liuzhou 545006 Peoples R China

Automatic parking system (APS) plays an important role in alleviating drivers' burden and improving vehicle safety. This study proposes a laser-based simultaneous localisation and mapping (SLAM) automatic parallel parking and tracking control scheme, which include environment perception and reconstruction, parking path planning, and path following. First, the proposed approach selects short-range lidar to enlarge its perceptron on parking environment and senses available parking space to build neighbourhood mapping with the help of simultaneous localisation. The test evaluation indicates that laser-SLAM has achieved good performance for recognising free spaces. Then, scene-dependent B-spline parallel parking path planning algorithm is proposed to optimise the parking path curve and makes the path meet vehicle kinematics model constrains well, in which vehicle actuator's dynamic performance and parking path smoothness are taken as key attributes. The experiment results indicate that the designed parallel parking path is better smooth. At last, a path following control method based on model predictive control (MPC) algorithm is proposed. The authors built an intelligent vehicle APS platform, and the results indicate that the designed MPC algorithms has excellent robustness and can minimise the tracking error. All the proposed scheme is quantitatively evaluated using different parking scene simulation with satisfactory performance.

关键词： collision avoidance path planning SLAM (robots) mobile robots predictive control automobiles vehicle dynamics splines (mathematics) laser-based SLAM automatic parallel parking path planning passenger vehicle automatic parking system tracking control scheme environment perception reconstruction parking environment laser-SLAM scene-dependent B-spline parallel parking path parking path curve vehicle kinematics model designed parallel parking path model predictive control algorithm intelligent vehicle APS platform different parking scene simulation vehicle safety laser-based simultaneous localisation and mapping available parking space sensing

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