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Stability and performance guarantees for model predictive control algorithms without terminal constraints

ZAMM-ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK 2014年第4期94卷 317-330页

作者： Pannek, Juergen Worthmann, Karl Univ Fed Armed Forces D-85577 Munich Germany TU Ilmenau D-98693 Ilmenau Germany

A typical bottleneck of model predictive control algorithms is the computational burden in order to compute the receding horizon feedback law which is predominantly determined by the length of the prediction horizon. Based on a relaxed Lyapunov inequality we present techniques which allow us to show stability and suboptimality estimates for a reduced prediction horizon. In particular, the known structural properties of suboptimality estimates based on a controllability condition are used to cut the gap between theoretic stability results and numerical observations.

关键词： Asymptotic stability feedback model predictive control algorithm performance receding horizon control

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

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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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Nonlinear observer output-feedback MPC treatment scheduling for HIV

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BIOMEDICAL ENGINEERING ONLINE 2011年第1期10卷 1-16页

作者： Zurakowski, Ryan Univ Delaware Dept Elect & Comp Engn Newark DE 19716 USA

Background: Mathematical models of the immune response to the Human Immunodeficiency Virus demonstrate the potential for dynamic schedules of Highly Active Anti-Retroviral Therapy to enhance Cytotoxic Lymphocyte-mediated control of HIV infection. Methods: In previous work we have developed a model predictive control (MPC) based method for determining optimal treatment interruption schedules for this purpose. In this paper, we introduce a nonlinear observer for the HIV-immune response system and an integrated output-feedback MPC approach for implementing the treatment interruption scheduling algorithm using the easily available viral load measurements. We use Monte-Carlo approaches to test robustness of the algorithm. Results: The nonlinear observer shows robust state tracking while preserving state positivity both for continuous and discrete measurements. The integrated output-feedback MPC algorithm stabilizes the desired steady-state. Monte-Carlo testing shows significant robustness to modeling error, with 90% success rates in stabilizing the desired steady-state with 15% variance from nominal on all model parameters. Conclusions: The possibility of enhancing immune responsiveness to HIV through dynamic scheduling of treatment is exciting. Output-feedback model predictive control is uniquely well-suited to solutions of these types of problems. The unique constraints of state positivity and very slow sampling are addressable by using a special-purpose nonlinear state estimator, as described in this paper. This shows the possibility of using output-feedback MPC-based algorithms for this purpose.

关键词： model predictive control Nonlinear Observer Viral Load Measurement model predictive control algorithm Structure Treatment Interruption

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Voltage and frequency control during microgrid islanding in a multi-area multi-microgrid system

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IET GENERATION TRANSMISSION & DISTRIBUTION 2017年第6期11卷 1502-1512页

作者： John, Thomas Lam, So Ping Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore

This study presents a control method to regulate load voltage and system frequency during microgrid is landing in a multi-area multi-microgrid (MMG) system. In the event of islanding of a microgrid from the distribution grid in the proposed MMG system, load voltage of the islanded microgrid and system frequency are affected. To overcome these problems, a control system for the MMG system is proposed. The proposed control system facilitates desired power exchange between grid-connected and islanded microgrids, and achieves effective voltage and frequency regulation in the MMG system. The main significance of the proposed MMG system is that multiple microgrids in different locations can be interconnected to meet larger bulk power demands. This ensures improved reliability and security of power supply in the MMG system. An improved model predictive control (MPC) algorithm is used to regulate various parameters such as output voltage, frequency and power of the inverters in the MMG system. The proposed MMG system is tested during islanding and load shedding using simulation studies. The simulation studies show that the inverters can operate effectively using MPC to provide the desired voltage, frequency and power during islanding and load shedding.

关键词： Optimal control reliability power system security control of electric power systems multiarea MMG system voltage control predictive control Power system management, operation and economics multiarea multimicrogrid system distributed power generation Power system control MPC algorithm power regulation power supply security power generation reliability power generation control microgrid islanding Voltage control system frequency regulation Reliability distribution grid load shedding Distributed power generation frequency control load voltage regulation Frequency control grid-connected microgrids model predictive control algorithm

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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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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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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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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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model predictive controller design for ship dynamic positioning system based on state-space equations

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY 2017年第3期22卷 426-431页

作者： Li, Wenhua Sun, Yuqing Chen, Haiquan Wang, Gang Dalian Maritime Univ Dept Marine Engn 1 Linghai Rd Dalian 116026 Liaoning Peoples R China

model predictive control (MPC) algorithm based on state-space equations was applied to ship dynamic positioning control system. A state estimator was designed to solve the problem that not all the states used can be measured to improve the control accuracy of the system. Through simulation in MATLAB(A (R)), this paper analyzed and compared the model predictive controller with or without constraints and the state estimator. Simulation results on a supply ship verify the effectiveness of this proposed model predictive control algorithm based on state-space equations and show that the MPC controller with the state estimator can improve the control effect of dynamic positioning system of ships.

关键词： Ship Dynamic positioning system model predictive control algorithm State-space equations The state estimator

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