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Dynamic modelling and parametric control for the polymer electrolyte membrane fuel cell system

JOURNAL OF POWER SOURCES 2013年 232卷 270-278页

作者： Zhao, Yuehong Pistikopoulos, Efstratios Chinese Acad Sci Inst Proc Engn State Key Lab Multiphase Complex Syst Beijing 100190 Peoples R China Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn London SW7 2AZ England

This paper addresses the development of a parametric controller for the Polymer Electrolyte Membrane (PEM) fuel cell system, and the investigation of its performance. First, the dynamic modelling is carried out to obtain the transient performance of the PEM fuel cell system and to form the basis for the controller design. Then, a parametric controller is designed to optimize its operation, focussing on tracking the output voltage and stack temperature set points by suitably manipulating the oxygen and hydrogen excess ratios, and cooling water flow rate. It is realized by formulating a Model Predictive Control (MPC) problem, which is solved via parametric programming technique to obtain the explicit control action function. The closed-loop simulation results show that the designed parametric controller can track the set points well, and ensures reliable performance in the presence of the current load fluctuations. Compared to proportional integral derivative controller (PID), it has the advantages of satisfying the imposed constraints, the potential of simple hydrogen control operation and lower hydrogen consumption. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Polymer electrolyte membrane fuel cell Dynamic modelling parametric control multi-parametric programming

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multi-objective blood glucose control for type 1 diabetes

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MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 2009年第3期47卷 343-352页

作者： Dua, Pinky Doyle, Francis J., III Pistikopoulos, Efstratios N. Univ Calif Santa Barbara Dept Chem Engn Santa Barbara CA 93106 USA Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2AZ England

For people with type 1 diabetes, automatic controllers aim to maintain the blood glucose concentration within the desired range of 60-120 mg/dL by infusing the appropriate amount of insulin in the presence of meal and exercise disturbances. Blood glucose concentration outside the desired range can be harmful to an individual's health but concentration below 60 mg/dL, a state known as hypoglycemia, is considered to be more harmful than the concentration above 120 mg/dL, a state known as hyperglycemia. In this paper, two techniques to address this issue within a multi-parametric model based control framework are presented. The first technique introduces asymmetry into the objective function to penalize the deviation towards hypoglycemia more than the deviation towards hyperglycemia. The second technique is based upon placing higher priority on satisfaction of constraints on hypoglycemia than on satisfaction of constraints on hyperglycemia. The performance of both the control techniques is analyzed and compared in the presence of disturbances.

关键词： Insulin delivery multi-parametric programming multi-parametric model based control multi-objective control

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Explicit model predictive control: A connected-graph approach

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AUTOMATICA 2017年 76卷 103-112页

作者： Oberdieck, Richard Diangelakis, Nikolaos A. Pistikopoulos, Efstratios N. Imperial Coll London Dept Chem Engn London England Texas A&M Univ Dept Chem Engn College Stn TX 77843 USA

The ability to solve model predictive control (MPC) problems of linear time-invariant systems explicitly and offline via multi-parametric quadratic programming (mp-QP) has become a widely used methodology. The most efficient approaches used to solve the underlying mp-QP problem are either based on combinatorial considerations, which scale unfavorably with the number of constraints, or geometrical considerations, which require heuristic tuning of the step-size and correct identification of the active set. In this paper, we describe a novel algorithm which unifies these two types of approaches by showing that the solution of a mp-QP problem is given by a connected graph, where the nodes correspond to the different optimal active sets over the parameter space. Using an extensive computational study, as well as the explicit MPC solution of a combined heat and power system, the merits of the proposed algorithm are clearly highlighted. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Explicit MPC multi-parametric programming Combined heat and power

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Design of multi-parametric NCO tracking controllers for linear dynamic systems

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COMPUTERS & CHEMICAL ENGINEERING 2016年第0期92卷 64-77页

作者： Sun, Muxin Chachuat, Benoit Pistikopoulos, Efstratios N. Imperial Coll London Ctr Proc Syst Engn Dept Chem Engn London SW7 2AZ England Texas A&M Univ McFerrin Dept Chem Engn College Stn TX 77843 USA

A methodology for combining multi-parametric programming and NCO tracking is presented in the case of linear dynamic systems. The resulting parametric controllers consist of (potentially nonlinear) feedback laws for tracking optimality conditions by exploiting the underlying optimal control switching structure. Compared to the classical multi-parametric MPC controller, this approach leads to a reduction in the number of critical regions. It calls for the solution of more difficult parametric optimization problems with linear differential equations embedded, whose critical regions are potentially nonconvex. Examples of constrained linear quadratic optimal control problems with parametric uncertainty are presented to illustrate the approach. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： multi-parametric programming NCO-tracking Feedback control Explicit MPC

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PAROC-An integrated framework and software platform for the optimisation and advanced model-based control of process systems

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CHEMICAL ENGINEERING SCIENCE 2015年 136卷 115-138页

作者： Pistikopoulos, Efstratios N. Diangelakis, Nikolaos A. Oberdieck, Richard Papathanasiou, Maria M. Nascu, Ioana Sun, Muxin Univ London Imperial Coll Sci Technol & Med Dept Chem Engn London SW7 2AZ England Texas A&M Univ Artie McFerrin Dept Chem Engn College Stn TX USA

In this paper we present the main foundations and features of an integrated framework and software platform that enables the use of model-based tools in design, operational optimisation and advanced control studies. A step-wise procedure is outlined involving (i) the development of a high-fidelity dynamic model, and its validation and model analysis, (ii) a model approximation step, including system identification, model reduction and global sensitivity analysis, (iii) a receding horizon modelling step for model-predictive control (MPC) and reactive scheduling, (iv) a suite of multi-parametric programming techniques for optimisation under uncertainty, explicit/multi-parametric MPC and state-estimation and (v) an 'in-silico' validation step for the derived optimisation, control and/or scheduling strategies to be analysed within the original high-fidelity model. The proposed software platform, PAROC, is also introduced and demonstrated in three different classes of process systems engineering applications;a combined heat and power energy system, a distillation column and a periodic purification process for biopharmaceuticals. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： multi-parametric programming Design and control Scheduling and Control Software platform

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A patchy approximation of explicit model predictive control

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INTERNATIONAL JOURNAL OF CONTROL 2012年第12期85卷 1929-1941页

作者： Hoai-Nam Nguyen Olaru, Sorin Hovd, Morten SUPELEC Syst Sci E3S Dept Automat Control Gif Sur Yvette France Norwegian Univ Sci & Technol Dept Engn Cybernet N-7034 Trondheim Norway

The explicit solution of multi-parametric optimisation problems (MPOP) has been used to construct an off-line solution to relatively small-and medium-sized constrained control problems. The control design principles are based on receding horizon optimisation and generally use linear prediction models for the system dynamics. In this context, it can be shown that the optimal control law is a piecewise linear (PWL) state feedback defined over polytopic cells of the state space. However, as the complexity of the related optimisation problems increases, the memory footprint and implementation of such explicit optimal solution may be burdensome for the available hardware, principally due to the high number of polytopic cells in the state-space partition. In this article we provide a solution to this problem by proposing a patchy PWL feedback control law, which intend to approximate the optimal control law. The construction is based on the linear interpolation of the exact solution at the vertices of a feasible set and the solution of an unconstrained linear quadratic regulator (LQR) problem. With a hybrid patchy control implementation, we show that closed-loop stability is preserved in the presence of additive measurement noise despite the existence of discontinuities at the switch between the overlapping regions in the state-space partition.

关键词： model predictive control multi-parametric programming smooth patchy Lyapunov function positively invariant set piecewise-linear control

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Dynamic modeling and explicit/multi-parametric MPC control of pressure swing adsorption systems

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JOURNAL OF PROCESS CONTROL 2011年第1期21卷 151-163页

作者： Khajuria, Harish Pistikopoulos, Efstratios N. Univ London Imperial Coll Sci Technol & Med Dept Chem Engn Ctr Proc Syst Engn London SW7 2AZ England

Pressure swing adsorption (PSA) is a flexible, albeit complex gas separation system. Due to its inherent nonlinear nature and discontinuous operation, the design of a model based PSA controller, especially with varying operating conditions, is a challenging task. This work focuses on the design of an explicit/multi-parametric model predictive controller for a PSA system. Based on a system involving four adsorbent beds separating 70% H-2, 30% CH4 mixture into high purity hydrogen, the key controller objective is to fast track H-2 purity to a set point value of 99.99%. To perform this task, a rigorous and systematic framework is employed. First, a high fidelity detailed dynamic model is built to represent the system's real operation, and understand its dynamic behavior. The model is then used to derive appropriate linear models by applying suitable system identification techniques. For the reduced models, a model predictive control (MPC) step is formulated, where latest developments in multi-parametric programming and control are applied to derive a novel explicit MPC controller. To test the performance of the designed controller, closed loop simulations are performed where the dynamic model is used as the virtual plant. Comparison studies of the derived explicit MPC controller are also performed with conventional PID controllers. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： PSA Explicit MPC System identification multi-parametric programming

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Real-Time Self-Dispatch of a Remote Wind-Storage Integrated Power Plant Without Predictions: Explicit Policy and Performance Guarantee

IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY

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IEEE OPEN ACCESS JOURNAL OF POWER AND ENERGY 2021年 8卷 484-496页

作者： Guo, Zhongjie Wei, Wei Chen, Laijun Chen, Yue Mei, Shengwei Tsinghua Univ State Key Lab Power Syst Dept Elect Engn Beijing 100084 Peoples R China New Energy Ind Res Ctr Xining 810016 Peoples R China Chinese Univ Hong Kong Dept Mech & Automat Engn Hong Kong Peoples R China

This paper investigates real-time self-dispatch of a remote wind-storage integrated power plant connecting to the main grid via a transmission line with a limited capacity. Because prediction is a complicated task and inevitably incurs errors, it is a better choice to make real-time decisions based on the information observed in the current time slot without predictions on the uncertain electricity price and wind generation in the future. To this end, the operation problem is formulated under the Lyapunov optimization framework to maximize the long-term time-average revenue of the wind-storage plant. Inter-temporal storage dynamics are represented by a virtual queue which is mean rate stable. An online method for real-time dispatch is proposed based on Lyapunov drift algorithm via a drift-minus-revenue function. The upper bound of such a function, which does not depend on future uncertainty, is minimized in each time slot. Explicit dispatch policies are obtained through multi-parametric programming technique so that no optimization problem is solved online. It is proved that the online algorithm can maintain all the constraints across the entire horizon and the expected optimality gap compared to the deterministic offline optimum with perfect uncertainty information is inversely proportional to the weight coefficient in the drift-minus-revenue function. Numerical tests using real wind and electricity price data validate the effectiveness and performance of the proposed method.

关键词： Energy storage Lyapunov optimization multi-parametric programming online dispatch prediction-free wind-storage plant

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Toward Fast Calculation of Probabilistic Optimal Power Flow

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第4期34卷 3286-3288页

作者： Lin, Wei Yang, Zhifang Yu, Juan Bao, Shiyuan Dai, Wei Chongqing Univ Chongqing 400044 Peoples R China

With the rapid growth of renewables, probabilistic optimal power flow (POPF) has become an important tool to analyze uncertainties in power systems. However, POPF calculation involves repeatedly solving the optimization problem. The computational efficiency has been a major bottleneck for its practical application in power industries. This letter proposes a novel method to significantly improve the efficiency of POPF calculation while maintaining the desired accuracy. The IEEE 30-bus, IEEE 118-bus, and practical utility 661-bus systems are used to demonstrate the effectiveness of the proposed method.

关键词： Fast calculation probabilistic optimal power flow (POPF) multi-parametric programming

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Incorporating External Flexibility in Generation Expansion Planning

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第6期36卷 5959-5962页

作者： Dai, Wei Shi, Bochen Zhang, Dongdong Goh, HuiHwang Liu, Hui Li, Jinghua Guangxi Univ Sch Elect Engn Nanning 530004 Peoples R China

Exploiting flexibilities (e.g., demand response, energy storage, and deep peak regulation.) in generation expansion planning (GEP) is significant for coping with the increase of renewable energy (RE). This letter presents a GEP model with novel consideration of the flexibility of the interconnected external network without data leakage. External flexibility (detailed information) is represented as a feasible region with generation cost functions related to tie-line power, by using multi-parametric programming. Numerical results demonstrate the effectiveness of the proposed model.

关键词： Mathematical model Generators Planning Load modeling Integrated circuit modeling Energy storage Cost function Generation expansion planning flexibility data privacy multi-parametric programming

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