• Title, Summary, Keyword: Predictive Control

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Design of Predictive Controller for Effective Superheat Control of Variable Speed Refrigeration System (가변속냉동시스템의 효율적인 과열도제어를 위한 예측제어기 설계)

  • Choi, Jeong-Pil;Hua, Li;Jeong, Seok-Kwon
    • Proceedings of the SAREK Conference
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    • pp.9-15
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    • 2008
  • In this paper, we suggest PI control with a predictive controller to progress both energy saving and coefficient of performance(COP) in a variable speed refrigeration system. The capacity and superheat are controlled simultaneously and independently by an inverter and an electronic expansion valve respectively for saving energy and improving COP in the system. The refrigeration system has long dead time in superheat inherently. The dead time makes the system difficult to achieve the satisfactory quick control response, especially superheat control response. In order to solve this problem, we designed a predictive controller based on PI control to progress superheat control performance. The control performance was investigated through some experiments to verify the effectiveness of the predictive controller.

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Design of a Nuclear Reactor Controller Using a Model Predictive Control Method

  • Na, Man-Gyun;Jung, Dong-Won;Shin, Sun-Ho;Lee, Sun-Mi;Lee, Yoon-Joon;Jang, Jin-Wook;Lee, Ki-Bog
    • Journal of Mechanical Science and Technology
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    • v.18 no.12
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    • pp.2080-2094
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    • 2004
  • A model predictive controller is designed to control thermal power in a nuclear reactor. The basic concept of the model predictive control is to solve an optimization problem for finite future time steps at current time, to implement only the first optimal control input among the solved control inputs, and to repeat the procedure at each subsequent instant. A controller design model used for designing the model predictive controller is estimated every time step by applying a recursive parameter estimation algorithm. A 3-dimensional nuclear reactor analysis code, MASTER that was developed by Korea Atomic Energy Research Institute (KAERI), was used to verify the proposed controller for a nuclear reactor. It was known that the nuclear power controlled by the proposed controller well tracks the desired power level and the desired axial power distribution.

Operation Analysis and New Current Control of Parallel Connected Dual Converter System without Interphase Reactors (상간리액터 없는 병렬연결 듀얼컨버터 시스템의 동작해석과 새로운 전류제어)

  • Ji, Jun-Geun
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.49 no.7
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    • pp.488-493
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    • 2000
  • In this paper, a predictive current control of 12-pulse parallel connected dual converter system without interphase reactors(IPR) is presented. Firstly, the characteristics of system without IPR are analyzed and compared with that of system with IPR. And the predictive current control of this system is discussed. Finally the validity of the presented system and the excellence of the predictive current control response is proved through the simulation results and experimental results.

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Simplified predictive control employing kalman filter

  • Shimizu, Hiroshi;Mori, Ryoichi
    • 제어로봇시스템학회:학술대회논문집
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    • pp.1879-1882
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    • 1991
  • Kalman Filter application to model predictive control is discussed. Most of refinery and petrochemical processes contain uncertainties in their output. Simplified state estimation algorithm is merged to model predictive control to improve overall control accuracy.

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Predictive Control for Electrical Drives-A Survey

  • Kennel Ralph;Linder Arne
    • Proceedings of the KIPE Conference
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    • pp.746-750
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    • 2001
  • During the last decades several proposals have been made in literature to use predictive control for inverter control-especially in electrical drives. These algorithms are completely different to the recursive but linear predictive algorithms known from information theory, where closed mathematical equations are used (e.g. Kalman-filters). Only few of the presented schemes have been realized in industrial applications so far. After some further progress, however, the advantage of predictive algorithms might lead to an increased number of industrial implementations in the future. Besides the common basic idea - to use the well-known but strongly non-linear behaviour of inverters to precalculate the best switching times - there are many differences in the details of these proposals. This contribution shows similarities and differences and attempts to design a 'family tree' of predictive control algorithms. This might grow to a first step to a theoretical approach to deal with predictive control schemes in a more generalised way.

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Pseudospectral Model Predictive Control for Exo-atmospheric Guidance

  • Rahman, Tawfiqur;Zhou, Hao;Yang, Liang;Chen, Wanchun
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.1
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    • pp.64-76
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    • 2015
  • This paper suggests applying pseudospectral model predictive method for exo-atmospheric guidance. The method is a fusion of pseudospectral law and model predictive control, in which a two point boundary value problem is formulated using model predictive approach and solved by applying pseudospectral law. In this work, the method is applied to exo-atmospheric guidance with specific target requirement. The existing exo-atmospheric guidance methods suffice general requirements for guidance, but cannot ensure specific target constraints; whereas, the presented method is able to do so. The proposed guidance law is assessed through simulation of perturbed cases, and the tests suggest that the method is able to operate semi-autonomously under control and thrust vector perturbations.

Robust Predictive Feedback Control for Constrained Systems

  • Giovanini, Leonardo;Grimble, Michael
    • International Journal of Control, Automation, and Systems
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    • v.2 no.4
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    • pp.407-422
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    • 2004
  • A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

A Model Predictive Controller for Nuclear Reactor Power

  • Na Man Gyun;Shin Sun Ho;Kim Whee Cheol
    • Nuclear Engineering and Technology
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    • v.35 no.5
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    • pp.399-411
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    • 2003
  • A model predictive control method is applied to design an automatic controller for thermal power control in a reactor core. The basic concept of the model predictive control is to solve an optimization problem for a finite future at current time and to implement as the current control input only the first optimal control input among the solutions of the finite time steps. At the next time step, the second optimal control input is not implemented and the procedure to solve the optimization problem is then repeated. The objectives of the proposed model predictive controller are to minimize the difference between the output and the desired output and the variation of the control rod position. The nonlinear PWR plant model (a nonlinear point kinetics equation with six delayed neutron groups and the lumped thermal-hydraulic balance equations) is used to verify the proposed controller of reactor power. And a controller design model used for designing the model predictive controller is obtained by applying a parameter estimation algorithm at an initial stage. From results of numerical simulation to check the controllability of the proposed controller at the $5\%/min$ ramp increase or decrease of a desired load and its $10\%$ step increase or decrease which are design requirements, the performances of this controller are proved to be excellent.

An Improved Predictive Control of an Induction Machine fed by a Matrix Converter for Torque Ripple Reduction (토크 리플 저감을 위한 매트릭스 컨버터 구동 유도 전동기의 향상된 예측 제어 기법)

  • Lee, Eunsil;Choi, Woo Jin;Lee, Kyo-Beum
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.7
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    • pp.662-668
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    • 2015
  • This paper presents an improved predictive control of an induction machine fed by a matrix converter using N-switching vectors as the control action during a complete sampling period of the controller. The conventional model predictive control scheme based matrix converter uses a single switching vector over the same period which introduces high torque ripple. The proposed switching scheme for a matrix converter based model predictive control of an induction machine drive selects the appropriate switching vectors for control of electromagnetic torque with small variations of the stator flux. The proposed method can reduce the ripple of the electrical variables by selecting the switching state as well as the method used in the space vector modulation techniques. Simulation results are presented to verify the effectiveness of the improved predictive control strategy for induction machine fed by a matrix converter.

Optimization of Mobile Robot Predictive Controllers Under General Constraints (일반제한조건의 이동로봇예측제어기 최적화)

  • Park, Jin-Hyun;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.4
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    • pp.602-610
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    • 2018
  • The model predictive control is an effective method to optimize the current control input that predicts the current control state and the future error using the predictive model of the control system when the reference trajectory is known. Since the control input can not have a physically infinitely large value, a predictive controller design with constraints should be considered. In addition, the reference model $A_r$ and the weight matrices Q, R that determine the control performance of the predictive controller are not optimized as arbitrarily designated should be considered in the controller design. In this study, we construct a predictive controller of a mobile robot by transforming it into a quadratic programming problem with constraints, The control performance of the mobile robot can be improved by optimizing the control parameters of the predictive controller that determines the control performance of the mobile robot using genetic algorithm. Through the computer simulation, the superiority of the proposed method is confirmed by comparing with the existing method.