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检索条件"主题词=Model predictive and optimization-based control"

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Sampling variance update method in Monte Carlo model predictive control 21st

Sampling variance update method in Monte Carlo Model Predict...

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Nakatani, Shintaro Date, Hisashi Univ Tsukuba Grad Sch Syst & Informat Engn Ibaraki Japan Univ Tsukuba Fac Engn Informat & Syst Ibaraki Japan

This study describes the influence of user parameters on control performance in a Monte-Carlo model predictive control (MCMPC). MCMPC based on Monte-Carlo sampling depends significantly on the characteristics of sampling distribution. We quantified the effect of user determinable parameters on control performance uisng the relatonship between the algorithm of MCMPC and convergence to the optimal solution. In particular, we investigated the limitations associated with the variance of sampling distribution causing a trade-off relationship with the convergence speed and accuracy of estimation. To overcome this limitation, we proposed two variance updating methods and new MCMPC algorithm. Furthermore, the effectiveness of the numeriacl simulation was verified. Copyright (C) 2020 The Authors.

关键词： Optimal control theory Monte-Carlo methods Randomized methods model predictive and optimization-based control

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Saving Tokens in Rollout control with Token Bucket Specification 21st

Saving Tokens in Rollout Control with Token Bucket Specifica...

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21st IFAC World Congress on Automatic control - Meeting Societal Challenges

作者： Jaumann, Florian Wildhagen, Stefan Allgoewer, Frank Univ Stuttgart Stuttgart Germany Univ Stuttgart Inst Syst Theory & Automat Control Stuttgart Germany

We consider a communication network over which transmissions must fulfill the so-called token bucket traffic specification, with a rollout (i.e., predictive) controller that both schedules transmissions and computes the corresponding control values. In the token bucket specification, a transmission is allowed if the current level of tokens is above a certain threshold. Recently, it has been shown that having a full bucket at the time of a set point change significantly improves the control performance as compared to when the bucket level is low. In this work, we develop mechanisms that guarantee that the bucket fills up after the controlled plant has converged to a set point. To do this, we consider two different setups. First, we consider that all transmissions over the network must fulfill the token bucket specification and show convergence to the upper sector of the bucket by adding a slight terminal cost on the bucket level. Afterwards, we consider a modified network which additionally features a direct link over which transmissions need not fulfill the token bucket specification. In this setup, we prove convergence of the bucket level exactly to the upper rim. These mechanisms enable a similar level of flexibility as event-triggered control: In converged state, little communication is used while in precarious operating conditions, a burst of transmissions is possible. Other than event-triggered approaches, the proposed methods allow to specify the network traffic beforehand by means of the token bucket. Lastly, we validate the proposed approaches in a numerical example. Copyright (C) 2020 The Authors.

关键词： control over networks control under communication constraints model predictive and optimization-based control

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

Model predictive control for rendezvous hovering phases base...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Gilz, Paulo Ricardo Arantes Joldes, Mioara Louembet, Christophe Camps, Frederic Univ Toulouse CNRS LAAS 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

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

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model predictive control of an Exothermic Pressure Leach Circuit

Model Predictive Control of an Exothermic Pressure Leach Cir...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Brooks, K. Burchell, J. Pieterse, F. BluESP Ltd 53 Platina StJukskei Pk ZA-2188 Randburg South Africa Lonmin Platinum Middelkraal Farm ZA-0284 Marikana 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

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

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Experimentally Validated model predictive controller for a Hexacopter

Experimentally Validated Model Predictive Controller for a H...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Ligthart, Jeroen A. J. Poksawat, Pakorn Wang, Liuping Nijmeijer, Henk Eindhoven Univ Technol Dept Mech Engn Eindhoven Netherlands RMIT Univ Sch Engn Melbourne Vic 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

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

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model predictive control of a Zinc Flotation Bank Using Online X-ray Fluorescence Analysers

Model Predictive Control of a Zinc Flotation Bank Using Onli...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Measurement and Instrumentation Identification and modelling Advanced Process control model predictive and optimization-based control Flotation

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predictive model based architecture for energy biomass supply chains tactical decisions

Predictive model based architecture for energy biomass suppl...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Pinho, Tatiana M. Coelho, Joao Paulo Veiga, Germano Paulo Moreira, A. Oliveira, Paulo Moura Boaventura-Cunha, Jose Univ Tras Os Montes & Alto Douro Escola Ciencias & Tecnol P-5001801 Vila Real Portugal Inst Politecn Braganca Escola Super Tecnol & Gestao Campus Sta Apolonia P-5300253 Braganca Portugal Univ Porto Fac Engn Oporto Portugal INESC TEC Technol & Sci Campus FEUP P-4200465 Oporto 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Production planning and control Job and activity scheduling modelling and control under change Adaptive control-applications model predictive and optimization-based control

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Economic MPC applied to generation scheduling in CSP plants

Economic MPC applied to generation scheduling in CSP plants

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Vasallo, M. J. Bravo, J. M. Marin, D. Gegundez, M. E. Univ Huelva ETSI Dept Ingn Elect Sistemas Informat & Automat 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Optimal operation and control of power systems Planning Energy market integration model predictive and optimization-based control modeling and simulation of power systems

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Improvements on Interpolation Techniques based on Linear Programming for Constrained control

Improvements on Interpolation Techniques based on Linear Pro...

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Rubin, Daniel Mercader, Pedro Hoai-Nam Nguyen Gutman, Per-Olof Banos, Alfonso Technion Israel Inst Technol Autonomous Syst Program Haifa Israel Univ Murcia Dept Comp & Syst Engn Murcia Spain IFP Energies Nouvelles Control Signal & Syst Dept Lyon France Technion Israel Inst Technol Fac Civil & Environm Engn 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. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

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

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Nested distributed MPC

Nested distributed MPC

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20th World Congress of the International-Federation-of-Automatic-control (IFAC)

作者： Monasterios, Pablo R. Baldivieso Hernandez, Bernardo Trodden, Paul A. Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD S Yorkshire England

We propose a distributed model predictive control approach for linear time-invariant systems coupled via dynamics. The proposed approach uses the tube MPC concept for robustness to handle the disturbances induced by mutual interactions between subsystems;however, the main novelty here is to replace the conventional linear disturbance rejection controller with a second MPC controller, as is done in tube-based nonlinear MPC. In the distributed setting, this has the advantages that the disturbance rejection controller is able to consider the plans of neighbours, and the reliance on explicit robust invariant sets is removed. (C) 2017, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： control of constrained systems Decentralized and distributed control Distributed control and estimation model predictive and optimization-based control

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