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4th International IEEE Conference Intelligent Systems

作者： Petrov, Michail Taneva, Albena Puleva, Teofana Ahmed, Sevil Tech Univ Sofia Dept Control Syst Branch Plovdiv Sofia Bulgaria

ISBN: (纸本)9781424417391

model predictive control (MPC) has been considered as the most important development in the area of process control in the last two decades. This paper addresses the issue of controlling a nonlinear plant by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy model is suggested as a means to model the plant with nonlinearities depending on the operating region. The developed model is used as a predictive model for a parallel distributed model predictive control algorithm. In this paper, the parallel distributed neuro-fuzzy model predictive controller has been proposed to control a non-linear control system of a hydro, turbine generator. The proposed technique has been tested and evaluated using this simulated industrial plant.

关键词： non-linear model predictive control Takagi-Sugeno fuzzy models fuzzy model predictive control turbine generator

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Decoupling Neuro-Fuzzy model predictive controllers Applied to Quadruple Tanks 8

Decoupling Neuro-Fuzzy Model Predictive Controllers Applied ...

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8th IEEE International Conference on Intelligent Systems (IS)

作者： Ahmed, Sevil Ganchev, Ivan Taneva, Albena Petrov, Michail Tech Univ Sofia Plovdiv Branch Control Syst Dept 25Tsanko Dyustabanov St Plovdiv 4000 Bulgaria

ISBN: (纸本)9781509013531

This paper is focused on the design of an algorithm for decoupling multivariable systems based on generalized predictive control and its application to control of a quadruple tank system. The quadruple-tank process is representative of a multivariable control problem that may be found in a chemical engineering process control application. To handle the nonlinearities, a Takagi-Sugeno neuro-fuzzy system is suggested to model the plant dynamics at relevant operating regions. The developed model is used as a predictive model for a decoupling model predictive control algorithm.

关键词： decoupling fuzzy-neural model predictive control non-linear model predictive control Takagi-Sugeno fuzzy models quadruple tanks

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control of Dual Stator Induction Generator Based Wind Energy Conversion System 4

Control of Dual Stator Induction Generator Based Wind Energy...

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4th IEEE-Nigeria-Section International Conference on Disruptive Technologies for Sustainable Development (IEEE NIGERCON)

作者： Abdulwahab, Ibrahim Abubakar, Adamu Saidu Olaniyan, Abdulrahman Sadiq, Bashir Olaniyi Faskari, Shehu A. Ahmadu Bello Univ Elect Engn Zaria Nigeria Kampala Int Univ Comp Engn Kampala Uganda Baze Univ Elect Engn Abuja Nigeria

ISBN: (纸本)9781665479783

The work presents a robust control scheme for a Dual Stator Induction Generator (DSIG) based Wind Energy Conversion System (WECS). This developed scheme mitigates deviations in torque and flux of the generator that occurs due to imbalance in the currents of the generator. The models developed comprises of a wind turbine system, a six phase SCIG, two - three phase converters for controlling the generator and a three-phase converter that connects the generator with the grid. A back-to-back voltage source converter was utilized for interfacing the DSIG with the grid. The non-linear model predictive control (NMPC) scheme was used for the control. All simulations were carried out in Matlab 2019b. The result obtained for the electromagnetic torque values obtained showed proper tracking of the reference torque, with an average percentage deviation of 17.11%. These minimal deviations were due to the large variations of the wind speed during these periods. While for the direct rotor flux, it was observed that, the flux settles at time 0.7 seconds which is well within the settling time limit. This showed that the developed scheme has properly decoupled the direct rotor flux from the quadratic rotor flux. For the grid side, the DC link voltage obtained has a settling time of 0.8 seconds, with a minimal overshoot.

关键词： Wind energy conversion system non-linear model predictive control Field Oriented control Dual Stator Induction Generator

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Greenhouse gases mitigation: global externalities and short-termism

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ENVIRONMENT AND DEVELOPMENT ECONOMICS 2023年第3期28卷 230-241页

作者： Di Bartolomeo, Giovanni Fard, Behnaz Minooei Semmler, Willi Sapienza Univ Rome Dept Econ & Law Rome Italy Univ Antwerp Dept Econ Antwerp Belgium Ca Foscari Univ Venice Dept Econ Venice Italy New Sch Social Res New York NY 10011 USA Univ Bielefeld Bielefeld Germany

Policies designed to control greenhouse gases imply domestic tradeoffs and international externalities, which lead to both domestic and international conflicts, influencing their feasibility and implementations. Our paper investigates two quantitative aspects within this debate. We intend to quantify the impact of: (a) the internalization of international externalities;and (b) the damage associated with a short-term view of climate policies. In this respect, we adopt the innovative (in this field) idea of model predictive control to formalize moving-horizon policy strategies and, thus, to build counterfactuals characterized by a different horizon for all policymakers.

关键词： climate policy CO2 concentration global warming non-linear model predictive control short-termism

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Visual predictive control of Robotic Arms with Overlapping Workspace 16

Visual Predictive Control of Robotic Arms with Overlapping W...

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16th International Conference on Informatics in control, Automation and Robotics (ICINCO)

作者： Le Flecher, E. Durand-Petiteville, A. Cadenat, V Sentenac, T. CNRS LAAS 7 Ave Colonel Roche F-31400 Toulouse France Univ Toulouse UPS F-31400 Toulouse France Fed Univ Pernambuco UFPE Mech Dept Recife PE Brazil

ISBN: (纸本)9789897583803

This paper deals with multi-arms fruits picking in orchards. More specifically, the goal is to control the arms to approach the fruits position. To achieve this task a VPC strategy has been designed to take into account the dynamic of the environment as well as the various constraints inherent to the mechanical system, visual servoing manipulation and shared workspace. Our solution has been evaluated in simulation using on PR2 arms model. Different models of visual features prediction have been tested and the entire VPC strategy has been run on various cases. The obtained results show the interest and the efficiency of this strategy to perform a fruit picking task.

关键词： Agricultural Robotics Multi-arms non-linear model predictive control Image based Visual Servoing

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Supervisory and temperature control of batch reactor by NMPC: An experimental study

Supervisory and temperature control of batch reactor by NMPC...

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European Symposium on Computer Aided Process Engineering-9 (Escape-9)

作者： Xaumier, F Ettedgui, B Le Lann, MV Cabassud, M Casamatta, G Inst Natl Polytech Toulouse Ecole Natl Super Ingn Genie Chim CNRSUMR 5503 Lab Genie Chim F-31078 Toulouse France

This paper describes the application of nonlinear model predictive control (NMPC) to the thermal control of a batch or semi-batch chemical reactor fitted with an alternative heating/cooling system. The strategy of the nonlinear control system is based on an open-loop constrained optimisation problem which is solved repeatedly on-line by a sequential optimisation and solution strategy on a PC for a typical temperature sampling rate. The feasibility of such a controller is examined on simulations and experiments on a 16 litres pilot plant. The presented results are satisfactory and are promising for an industrial use of such a technique.

关键词： batch chemical system non-linear model predictive control optimisation temperature control fine chemicals

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A novel Economic nonlinear model predictive controller for power maximisation on wind turbines

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2022年 170卷

作者： Pustina, L. Biral, F. Serafini, J. Roma Tre Univ Dept Engn Rome Italy Univ Trento Dept Mech & Struct Engn Trento Italy

Reducing the Levelized Cost of Energy (LCoE) is one of the main objectives of the wind turbine industry. There are several ways to achieve this goal: reducing construction and installation costs, reducing Operat-ing&Maintenance costs, or increasing the power output. In this work, an Economic nonlinear model predictive control strategy is developed to maximise the power production of wind turbines. A novel three-states, non-linear Reduced Order model is developed to predict aerodynamic power, rotor thrust and generator temperature with suitable accuracy. The control action is obtained from a constrained optimisation problem that uses the developed model, where the objective is the maximisation of the integral of the aerodynamic power. A set of constraints (including a bound on the generator temperature and the rotor thrust) are imposed. First, the turbine model is validated against high-fidelity simulations, then the controller performance and robustness are assessed in the entire wind range of operation, obtaining a significant increase of average power. Apart from the assessment of the controller performance in OpenFAST, the controller robustness is verified, introducing errors in the estimation of incoming wind, up to the case of a complete lack of information. The controller (freely downloadable from a dedicated repository) is effective in all the operating regions without the need for logical switches. Moreover, thanks to the optimised numerical solver adopted, it can be applied to actual wind turbines (which require real-time algorithmic performance).

关键词： Wind turbine control Power maximisation non-linear model predictive control non-linear Reduced Order model

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A fast implementation of coalitional model predictive controllers based on machine learning: Application to solar power plants

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年 118卷

作者： Masero, Eva Ruiz-Moreno, Sara Frejo, Jose Ramon D. Maestre, Jose M. Camacho, Eduardo F. Univ Seville Dept Ingn Sistemas & Automatica C-Camino Descubrimientos S-N Seville 41092 Spain

This article proposes a real-time implementation of distributed model predictive controllers to maximize the thermal energy generated by parabolic trough collector fields. For this control strategy, we consider that each loop of the solar collector field is individually managed by a controller, which can form coalition with other controllers to attain its local goals while contributing to the overall objective. The formation of coalitions is based on a market-based mechanism in which the heat transfer fluid is traded. To relieve the computational burden online, we propose a learning-based approach that approximates optimization problems so that the controller can be applied in real time. Finally, simulations in a 100 -loop solar collector field are used to assess the coalitional strategy based on neural networks in comparison with the coalitional model predictive control. The results show that the coalitional strategy based on neural networks provides a reduction in computing time of up to 99.74% and a minimal reduction in performance compared to the coalitional model predictive controller used as the baseline.

关键词： Neural networks Artificial intelligence non-linear model predictive control Coalitional control Multi-agent systems Solar thermal applications

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Improving path-tracking performance of an articulated tractor-trailer system using a non-linear kinematic model

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2022年 196卷 106826-106826页

作者： Murillo, M. Sanchez, G. Deniz, N. Genzelis, L. Giovanini, L. Ciudad Univ UNL Res Inst Signals Syst & Computat Intelligence FICH UNL CONICET 4 Piso FICH RA-3000 Santa Fe S Argentina Univ Nacl Litoral UNL Fac Engn & Water Resources FICH RA-3000 Santa Fe S Argentina

This paper presents a novel non-linear mathematical model of an articulated tractor-trailer system that can be used, in combination with receding horizon techniques, to improve the performance of path tracking tasks of articulated systems. Due to its dual steering mechanisms, this type of vehicle can be very useful in precision agriculture, particularly for seeding, spraying and harvesting in small fields. The articulated tractor-trailer system model was embedded within a non-linear model predictive controller and the trailer position was monitored. When the kinematic of the trailer was considered, the deviation of trailer's position was reduced substantially alongside not only straight paths but also in headland turns. Using the proposed mathematical model, we were able to control the trailer's position itself rather than the tractor's position. The Robot Operating System (ROS) framework and Gazebo simulator were used to perform realistic simulations examples.

关键词： Tractor-trailer system Articulated vehicle Kinematic model non-linear model predictive control

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An optimal charging algorithm to minimise solid electrolyte interface layer in lithium-ion battery

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JOURNAL OF POWER SOURCES 2021年 482卷 228895-228895页

作者： Malik, M. S. S. Li, Guang Chen, Zheng Queen Mary Univ London Sch Engn & Mat Sci London E1 4NS England

This article presents a novel control algorithm for online optimal charging of lithium-ion battery by explicitly incorporating degradation mechanism into control, to reduce the degradation process. The health of battery directly relates to degradation and capacity fade in cycles of charging. We mainly focus on the growth the solid electrolyte interface (SEI) layer, which is the primary source of degradation of batteries. This article addresses the challenge of minimising SEI layer growth during charging by incorporating the first-order layer growth rate model into a non-linear model predictive control approach. A single particle model (SPM) is used for optimal charging using orthogonal projection-based model reformulation. Gauss pseudo-spectral method is used for the optimisation of charging trajectories. Results of the optimal algorithm are compared with the traditional constant current constant voltage (CCCV) approach without considering SEI layer growth. is ensured that overpotential caused by lithium plating remains in a healthy regime which is another feature the proposed strategy. Simulation results are presented to demonstrate the advantages of the proposed charging method.

关键词： Optimal charging non-linear model predictive control Lithium-ion battery Pseudo-spectral methods

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