• 제어로봇시스템학회논문지
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• 제2권4호
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• pp.344-350
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• 1996

An adaptive predictive level control of waste heat steam boiler was studied by using mathematical models considering the inverse response. The simulation experiments of the model identification were performed by using linear and bilinear models. From the results of simulations it was found that the bilinear model represented the actual dynamic behavior of steam boiler very well. ARMA model was used in the model identification and the adaptive predictive controller. To verify the performance and effectiveness of the adaptive predictive controller used in this study the simulation results of the adaptive predictive level control for waste heat steam boiler based on bilinear model were compared to those of P, PI and PID controller. The results of simulations showed that the adaptive predictive controller provides the fast arrival to setpoint of liquid level.

• 제어로봇시스템학회지
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• 제2권1호
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• pp.59-71
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• 1996

In the last decade, the model predictive control methods have enjoyed many industrial applications with successful results. Although the general predictive control methods for nonlinear chemical processes are not yet formulated, the promising features of the model predictive control methods attract attentions of many researchers who are involved with difficult but important nonlinear process control problems. Recently, the class of bilinear model has been introduced as an useful tool for examining many nonlinear phenomena. Since their structural properties are similar to those of linear models, it is not difficult to develop a robust adaptive model predictive control method based on bilinear model. We expect that the model predictive control method based on bilinear model will expand its region in the world of nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.156-159
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• 1996

An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

• Journal of Power Electronics
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• 제19권2호
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• pp.497-508
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• 2019

The predictive speed control (PSC) strategy can realize the simultaneous control of speed and current by using one cost function. As a model-based control method, the performance of the PSC is vulnerable to model mismatches such as load torque disturbances and parameter uncertainties. To solve this problem, this paper presents a robust predictive speed control (RPSC) strategy for surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed RPSC uses extended state observers (ESOs) to estimate the lumped disturbances caused by load torque changes and parameter mismatches. The observer-based prediction model is then compensated by using the estimated disturbances. The introduction of ESOs can achieve robustness against predictive model uncertainties. In addition, a modified cost function is designed to further suppress load torque disturbances. The performance of the proposed RPSC scheme has been corroborated by experimental results under the condition of load torque changes and parameter mismatches.

• 드라이브 ㆍ 컨트롤
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• 제16권2호
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• Transactions on Control, Automation and Systems Engineering
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• 제2권4호
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• pp.221-227
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• 2000

This paper combines the constrained model predictive control with the feedback linearization to solve a nonlinear system control problem with input constraints. The combined approach consists of two steps: Firstly, the nonlinear model is linearized by the feedback linearization. Secondly, based on the linearized model, the constrained model predictive controller is designed taking input constraints into consideration. The proposed controller is applied to two link robot system, and tracking performances of the controller are investigated via some simulations, where the comparisons are done for the cases of unconstrained, constrained input in feedback linearization.

• 한국컴퓨터정보학회논문지
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• 제28권12호
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• pp.231-238
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• 2023

부스트 PFC (Power Factor Correction)컨버터는 AC 입력 전류의 단일 역률과 낮은 THD (Total Harmonic Distortion)를 달성하기 위해 다양한 제어기법들이 연구되고 있다. 그중 인덕터 전류의 평균값을 전류지령에 추종하도록 제어하는 평균전류 모드 제어가 있으며 가장 널리 사용되고 있다. 하지만, 오늘날 디지털 프로세서의 발달로 고도화된 디지털 제어가 가능해지면서 부스트 PFC 컨버터의 예측제어가 관심을 받고 있다. 예측제어에는 예측 알고리즘으로 듀티를 미리 생성하는 예측전류 모드 제어 및 모델을 기반으로 한 비용함수를 선정하여 스위칭 동작을 하는 모델예측제어로 분류된다. 따라서 본 논문에서는 부스트 PFC 컨버터의 평균전류 모드 제어, 예측전류 모드 제어, 모델예측 전류 제어를 간단히 설명한다. 또한, 시뮬레이션을 통해 전체 부하 및 다양한 외란 조건에서의 전류 제어를 비교 분석한다.

• Journal of Power Electronics
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• 제17권4호
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• pp.983-990
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• 2017

This paper proposes a model predictive control based on the discrete Lyapunov function to improve the performance of power electronic converters. The proposed control technique, based on the finite control set model predictive control (FCS-MPC), defines a cost function for the control law which is determined under the Lyapunov stability theorem with a control error compensation. The steady state and dynamic performance of the proposed control strategy has been tested under a single phase AC/DC voltage source rectifier (S-VSR). Experimental results demonstrate that the proposed control strategy not only offers global stability and good robustness but also leads to a high quality sinusoidal current with a reasonably low total harmonic distortion (THD) and a fast dynamic response under linear loads.

• 대한임베디드공학회논문지
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• 제17권2호
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• pp.115-121
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• 2022

This paper proposes a distributed model predictive formation control algorithm for a group of unmanned ground vehicles (UGVs) with guaranteeing collision avoidance between UGVs. Generally, the model predictive control based formation control has a disadvantage in that it takes a long time to compute control inputs when considering collision avoidance between UGVs. In this paper, in order to overcome this problem, the formation control algorithm is implemented in a distributed manner so that it could be individually controlled. Also, a collision-avoidance method considering real-time is proposed. The proposed formation control algorithm is implemented based on robot operating system (ROS), open source-based middleware. Through the various simulation tests, it is confirmed that the formation control of five UGVs is successfully performed while avoiding collisions between UGVs.

• 전기학회논문지
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• 제60권2호
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• pp.383-388
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• 2011

In this paper, we consider Hammerstein-Wiener nonlinear model for solid oxide fuel cell (SOFC). A nonlinear model predictive control (MPC) is proposed to trace the constant stack terminal power by Hydrogen flow as control input. After the stability of the closed-loop system with static output feedback controller is analysed by Lyapunov method, a nonlinear model predictive control based on the Hammerstein-Wiener model is developed to control the stack terminal power of the SOFC system. Simulation results verify the effectiveness of the proposed control method based on the Hammerstein-Wiener model for SOFC system.