• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 A
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• pp.391-393
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• 1995

An improved predictive control technique using adaptive load estimation is proposed. The conventional predictive control technique has not concerned load variations and system parameters. Thus control performances are undesirable such as large current ripples and offset. In this paper the proposed controller employing a simple adaptive algorithm to estimate load is expected to be useful to overcome the problems of conventinal predictive controller.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2015년도 추계학술대회 논문집
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• pp.209-210
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• 2015

This paper presents a new model predictive control method without the effect of a weighting factor in order to reduce common-mode voltage (CMV) for a three-phase voltage source inverter (VSI). By utilizing two active states with same dwell time during a sampling period instead of one state used in conventional method, the proposed method can reduce the CMV of VSI without the weighting factor. Simulation is carried out to verify the effectiveness of the proposed predictive control method with the aid of PSIM software.

• Journal of Power Electronics
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• 제18권3호
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• pp.789-801
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• 2018

Model predictive direct power control (MPDPC) is a widely recognized high-performance control strategy for a three-phase grid-connected pulse width modulation (PWM) rectifier. Unlike those of conventional grid-connected PWM rectifiers, the active and reactive powers of permanent magnet synchronous generator (PMSG)-connected PWM rectifiers, which are used in electromagnetic transmitters, cannot be calculated as the product of voltage and current because the back electromotive force (EMF) of the generator cannot be measured directly. In this study, the predictive power model of the rectifier is obtained by analyzing the relationship among flux, back EMF, active/reactive power, converter voltage, and stator current of the generator. The concept of duty cycle control in the proposed MPDPC is introduced by allocating a fraction of the control period for a nonzero vector and rest time for a zero vector. When nonzero vectors and their duration in the predefined cost function are simultaneously evaluated, the global power ripple minimization is obtained. Simulation and experimental results prove that the proposed MPDPC strategy with duty cycle control for the PMSG-connected PWM rectifier can achieve better control performance than the conventional MPDPC-SVM with grid-connected PWM rectifier.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.429-434
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• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.

• 설비공학논문집
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• 제13권3호
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• pp.200-208
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• 2001

In indoor temperature control of a heat pump, a reduction in energy consumption is very important. However, most control schemes for heat pumps have focused only on control performance such s settling time and steady-state error. In this paper, the model predictive control (MPC) which includes the energy-related variable in this cost function is proposed. By computing the control signal minimizing this cost function, the trade-off between energy reduction and temperature control performance can be obtained. Since the MPC required the process model, the dynamic mode of a heat pump is also obtained by the system identification technique. Performance of the proposed MPC considering energy efficiency is compared with the two other control schemes. It si shown that the proposed scheme can consume less energy thant hte others in achieving similar control performance.

• 제어로봇시스템학회논문지
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• 제7권12호
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• pp.967-972
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• 2001

In this paper, an adaptive robust nonlinear predictive controller is developed for the continuous time nonlinear systems whose control objective is composed of the system output and its desired value. The basic control law is derived from the continuous time prediction model and its feedback dynamcis shows another from if input and output linearization. In order to cope with the parameter uncertainty, robust control is incorporated into the basic control law and the asymptotic convergence of tracking error to a certain bounded region is guaranteed. For stability and performance improvement within the bounded region, an adaptive control is introduced. Simulation tests for the motion control of an underwater wall-ranging robot confirm the performance improvement and the robustness of this controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.299-302
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• 1996

A control algorithm is proposed for nonlinear multi-input multi-output(MIMO) batch processes by combining quadratic iterative learning control(Q-ILC) with model predictive control(MPC). Both controls are designed based on output feedback and Kalman filter is incorporated for state estimation. Novelty of the proposed algorithm lies in the facts that, unlike feedback-only control, unknown sustained disturbances which are repeated over batches can be completely rejected and asymptotically perfect tracking is possible for zero random disturbance case even with uncertain process model.

• 전력전자학회논문지
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• 제19권3호
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• pp.249-256
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• 2014

This paper proposes a torque control method of permanent magnet synchronous motor, which has small torque ripple. The proposed control method is using the finite control set-model predictive control(FCS-MPC) strategy. An optimal input voltage vector minimizing a cost function is chosen among 6 passible active input voltage vectors following the FCS-MPC strategy. Then, a modulation factor for the optimal input voltage vector is computed to minimize the torque ripple. Thus, the proposed control method yields fast torque response and small torque ripple. The efficacy of the proposed method was verified through simulation and experiment.

• Journal of Power Electronics
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• 제18권5호
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• pp.1398-1408
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• 2018

In order to further improve the steady-state control performance of model predictive torque control (MPTC), a double-vector-based model predictive torque control without a weighting factor is proposed in this paper. The extended voltage vectors synthesized by two basic voltage vectors are used to increase the number of feasible voltage vectors. Therefore, the control precision of the torque and the stator flux along with the steady-state performance can be improved. To avoid testing all of the feasible voltage vectors, the solution of deadbeat torque control is calculated to predict the reference voltage vector. Thus, the candidate voltage vectors, which need to be evaluated by a cost function, can be reduced based on the sector position of the predicted reference voltage vector. Furthermore, a cost function, which only includes a reference voltage tracking error, is designed to eliminate the weighting factor. Moreover, two voltage vectors are applied during one control period, and their durations are calculated based on the principle of reference voltage tracking error minimization. Finally, the proposed method is tested by simulations and experiments.

• International Journal of Control, Automation, and Systems
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• 제4권6호
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• pp.669-681
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• 2006

In this work, a new method of design adaptive controllers for SISO systems based on multiple models and switching is presented. The controller selects the model from a given set, according to a switching rule based on output prediction errors. The goal is to design, at each sample instant, a predictive control law that ensures the robust stability of the closed-loop system and achieves the best performance for the current operating point. At each sample the proposed control scheme identifies a set of linear models that best characterizes the dynamics of the current operating region. Then, it carries out an automatic reconfiguration of the controller to achieve the best possible performance whilst providing a guarantee of robust closed-loop stability. The results are illustrated by simulations a nonlinear continuous and stirred tank reactor.