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第三十八届中国控制会议

作者： Xiaojun Zhou School of Automation Central South University

The canonical proportional-integral-derivative(PID) control approach has been widely used in industrial application due to their simplicity and ease of use. However, its corresponding controller parameters are hard to be adjusted, especially for nonlinear systems. The optimization-based method provides a general framework to find optimal PID controller parameters;nevertheless, several disadvantages exist, for example, it is nontrivial to select an appropriate sample size and it is necessary to obtain the global optimal solution but the optimization problem is non-convex, making it hard to achieve. To alleviate the aforementioned limitations, a rolling PID control approach is proposed in this study, in which, at each rolling period, the PID controller parameters are updated using observable data, which can be classified to data-driven control method. The effectiveness of the proposed approach has been validated by experiments.

关键词： Rolling PID control optimization-based control Data-driven control Nonlinear system control

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Experimentally Validated Model Predictive controller for a Hexacopter

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IFAC-PapersOnLine 2017年第1期50卷 4076-4081页

作者： Ligthart J.A.J. Poksawat P. Wang L. Nijmeijer H. Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands School of Engineering RMIT University Melbourne Australia

In recent years, Unmanned Aerial Vehicles (UAVs) have become feasible solutions to various applications such as military flight missions, search and rescue operations, and geological mapping. The attitude control systems for UAVs need to be very robust to ensure safe and stable flights. To improve the stability beyond conventional control methods, a novel Model Predictive control (MPC) formulation is proposed. In this paper, the mathematical derivation of the MPC controller is discussed. The novelty lies in the three-termed MPC cost function for attitude flight stability. The control strategy introduced in this paper is validated with experiments on a hexacopter in a custom fabricated experimental rig and with outdoor flight tests. The results show that the UAV is able to follow the operator's aggressive manoeuvring commands. based on the data obtained, the MPC controller appears to be a promising control method to improve UAVs’ performance. © 2017

关键词： Anti-windup control of constrained systems Disturbance rejection Model predictive Optimal control theory optimization-based control UAVs

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Model Predictive control of a Zinc Flotation Bank Using Online X-ray Fluorescence Analysers

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IFAC-PapersOnLine 2017年第1期50卷 10214-10219页

作者： Brooks K.S. Koorts R. BluESP 53 Platina St Randburg South Africa

In the metals and mining industry, flotation plays a vital role in selectively concentrating and separating valuable minerals from gangue minerals in a process slurry. The control of flotation circuits has proved difficult in the past, with large variations in reagent dosages, concentrate grade and the recovery of the valuable minerals being experienced. At Glencore's Mt Isa site, the control issues have been addressed using model predictive control (MPC). The MPC makes use of online grade analysers for precise control and an optimising controller engine for driving the process to an optimal state. The use of the analysers has introduced challenges associated with their relatively slow frequency, and the need to employ sensor validation for the measurements. © 2017

关键词： Advanced Process control Flotation Identification Instrumentation Measurement Model predictive Modelling optimization-based control

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Optimal partitioning of a boiler-turbine unit for Fuzzy model predictive control

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IFAC-PapersOnLine 2017年第1期50卷 2011-2016页

作者： Killian M. Kozek M. Vienna University of Technology Institute of Mechanics and Mechatronics Austria

In order to effectively control the multi-input multi-output (MIMO) characteristics of a boiler-turbine unit Fuzzy model predictive control (FMPC) has been previously applied successfully. An important step in the FMPC design is the partitioning (also called the design of the antecedent rules). In this work it is shown that by exploiting the plant characteristics and by using suitable metrics of the nonlinearity a representative one-dimensional partition space can be defined. Furthermore, it is demonstrated that a simple partition into two linear models suffices to obtain a stable and performing control system. In order to achieve this simple FMPC a nonlinear stationary feed-forward decoupling is implemented. Simulation results demonstrate stability and performance of the resulting control system even for large reference steps. The methodology developed in this work is quite general and can be easily applied to the FMPC design for other nonlinear MIMO plants. © 2017

关键词： Intelligent control of power systems Model predictive Modeling Nonlinear predictive control optimization-based control simulation of power systems

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Improvements on Interpolation Techniques based on Linear Programming for Constrained control

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IFAC-PapersOnLine 2017年第1期50卷 1403-1408页

作者： Rubin D. Mercader P. Nguyen H.-N. Gutman P.-O. Baños A. Autonomous Systems Program Technion – Israel Institute of Technology Haifa Israel Department of Computer and System Engineering University of Murcia Murcia Spain Control Signal and System Department IFP Energies Nouvelles Lyon France Faculty of Civil and Environmental Engineering Technion – Israel Institute of Technology Haifa Israel

We present some improvements on interpolation based control (IC) for linear discrete-time systems with polyhedral constraints on the control and the states variables. The plant may be uncertain, time-varying, and subject to bounded disturbances. Roughly speaking, IC approach is based on the interpolation between an inner and an outer controller. The extension presented here is twofold. On the one hand, the IC approach is extended to deal with higher order inner controllers, making it e.g. possible to incorporate integral action in a vicinity of the origin. On the other hand, this paper presents a modification that better exploits the control signal range. As with previous IC strategies, the presented method demands relatively low online computational resources, and is applicable also to uncertain plants. The benefits of the improved scheme are illustrated in some examples. © 2017

关键词： Constrained control Linear programing Model predictive optimization-based control Robust control Time-varying systems

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Model Predictive control for Hydronic Heating Systems in Residential Buildings

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IFAC-PapersOnLine 2017年第1期50卷 4216-4221页

作者： Fielsch S. Grunert T. Stursberg M. Kummert A. School of Electrical Information and Media Engineering Communication Theory University of Wuppertal Wuppertal D-42119 Germany Vaillant GmbH Remscheid D-42859 Germany

This paper aims at transferring the benefits reported on model predictive control (MPC) for office buildings to residential buildings. A modular modeling approach for heating systems and a modified control design is proposed. The advantages of the attempt of particularly taking the hydraulic domain into account in the MPC law are shown and a comparison with a standard controller is done via simulation. © 2017

关键词： Building Automation Industrial applications of optimal control Model predictive Modeling for control optimization optimization-based control

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Model Predictive control of an Exothermic Pressure Leach Circuit

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IFAC-PapersOnLine 2017年第1期50卷 10232-10237页

作者： Brooks K. Burchell J. Pieterse F. BluESP Limited 53 Platina Street Jukskei Park Randburg 2188 South Africa Lonmin Platinum Middelkraal Farm Marikana 0284 South Africa BluESP Limited South Africa

The pressurized Cu-Ni leach at Lonmin Platinum's Base Metal Refinery is highly exothermic with excessive temperatures risking damage to its reactors. Moreover, a study of the reaction kinetics of this leach showed that higher temperatures negatively impact its precious metal recovery. As a result, the production rate of the plant is limited by the rate at which this leach can be cooled and by the quality of its temperature control. Flash cooling was introduced and significantly increased the circuit's cooling potential; however, this modification resulted in circuit's control problem gaining multivariable complexity. We present here a model predictive controller that addressed these multivariable control challenges. Since the introduction of this controller a 9% improvement in the circuit's throughput potential was observed together with a significant increase in its precious metal recovery. © 2017

关键词： Advanced process control industrial applications of process control model predictive optimization-based control

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Predictive model based architecture for energy biomass supply chains tactical decisions

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IFAC-PapersOnLine 2017年第1期50卷 7681-7686页

作者： Pinho T.M. Coelho J.P. Veiga G. Moreira A.P. Oliveira P.M. Boaventura-Cunha J. Universidade de Trás-os-Montes e Alto Douro Escola de Ciências e Tecnologia Quinta de Prados Vila Real 5001-801 Portugal INESC TEC Technology and Science Campus da FEUP Porto 4200 -465 Portugal Instituto Politecnico de Bragança Escola Superior de Tecnologia e Gestao Campus de Sta. Apolónia Bragança 5300-253 Portugal Faculty of Engineering University of Porto Porto Portugal

Renewable sources of energy play a decisive role in the current energetic paradigm to mitigate climate changes associated with greenhouse gases emissions and problems of energy security Biomass energy and in particular forest wood biomass supply chains have the potential to enhance these changes due to its several benefits such as ability to produce both bioenergy and bioproducts, generate energy on-demand, among others. However, this energy source has some drawbacks mainly associated with the involved costs. In this work, the use of a Model Predictive control approach is proposed to plan, monitor and control the wood-biomass supply chain for energy production at a tactical level. With this methodology the biomass supply chain becomes more efficient ensuring the service quality in a more competitive way. In order to test and validate the proposed approach different simulation scenarios were considered that proved the efficiency of the proposed tool regarding the decisions definition and control. © 2017

关键词： activity scheduling Adaptive control-applications control control under change Job Model predictive Modelling optimization-based control Production planning

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Economic MPC applied to generation scheduling in CSP plants

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IFAC-PapersOnLine 2017年第1期50卷 115-120页

作者： Vasallo M.J. Bravo J.M. Marín D. Gegúndez M.E. Departamento de Ingeniería Electrónic de Sistemas Informáticos y Automática ETSI Universidad de Huelva Spain

This paper proposes a model-based predictive control (MPC) approach with economic objective function to face the scheduling problem in concentrating solar power (CSP) plants with thermal energy storage (TES) in a day-ahead energy market context. By this approach, the most recent energy prices, weather forecast and the current plant's state can be used by the proposed economic MPC approach to reschedule the generation conveniently from time to time. The proposed approach is applied, in a simulation context, to a 50 MW parabolic trough collector-based CSP with TES under the assumption of perfect price forecast and participation in the Spanish day-ahead energy market. A case study based on a four-month period to test several meteorological conditions is performed. In this study, a complete economic analysis is carried out using actual values of energy price, penalty cost, solar resource data and its forecast. Results show an economic improvement in comparison with a traditional day-ahead scheduling strategy. © 2017

关键词： control of power systems Energy market integration Model predictive Modeling Optimal operation optimization-based control Planning simulation of power systems

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Model predictive control for rendezvous hovering phases based on a novel description of constrained trajectories

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IFAC-PapersOnLine 2017年第1期50卷 7229-7234页

作者： Gilz P.R.A. Joldes M. Louembet C. Camps F. LAAS Université de Toulouse CNRS Toulouse France

The present article proposes a predictive control law for orbital spacecraft rendezvous hovering phases. An innovative description of periodic space-restricted trajectories based on computing the envelope of a family of curves is given. This description is used to provide a model predictive controller able to minimize the fuel consumption and account for convex constraints, such as periodicity, saturation of the thrusters and space restrictions. The efficiency of this control algorithm is assessed on a board simulating the performance of devices usually employed in space applications. © 2017

关键词： Aerospace control of vehicles Convex optimization FPGA embedded control law Guidance Model predictive navigation optimization-based control

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