• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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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.

• Proceedings of the KIPE Conference
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• 2001.10a
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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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.167-175
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• 2007

A predictive pulse control strategy as a means of improving the energy efficiency of radiant floor heating systems is explored. Experiments at the apartment with floor heating system are conducted to assess and compare the energy performance of the predictive pulse control strategy with an existing conventional control strategy. The Results showed that new suggested PPCM( Predictive Pulse Control Method) was available to decrease the gap of $1{\sim}1.5^{\circ}C$ between maximum and minimum indoor temperature of each rooms. Therefore PPCM method was favor to radiant floor heating system which have a delay time of 10-20 minutes for heat transfer by floor layers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.311-318
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• 2016

This paper is a study on the neutral point voltage balancing of the three-phase 3-level T-type inverter using the predictive control techniques. Recently, multi-level inverter has been attracting attention as the advantages such as efficiency improving and harmonic reduction. Especially, the T-type inverter topology is advantageous in low DC-link voltage. However, in case of the prediction control, it takes a lot of time, because there exist 27 voltage vectors and it has to be calculated according to the respective voltage vectors. Therefore, in this paper, we propose a method to implement predictive control techniques while reducing the operation time. In order to reduce the operation time, the predictive control is implemented by using the minimum voltage vector except for the unnecessary voltage vector. The result of the implemented predictive control is added to the SPWM by using the offset voltage. It was verified through simulation and experimental results.