• Journal of Power Electronics
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• 제17권3호
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• pp.674-685
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• 2017

The conventional model predictive direct torque control (MPDTC) method uses all of the voltage vectors available from a two level voltage source inverter for the prediction of the stator flux and stator current, which leads to a heavy computational burden. This paper proposes an improved model predictive direct torque control method. The stator flux predictive controller is obtained from an analysis of the relationship between the stator flux and the torque, which can be used to calculate the desired voltage vector based on the stator flux and torque reference. Then this method only needs to evaluate three voltage vectors in the sector of the desired voltage vector. As a result, the computational burden of the conventional MPDTC is effectively reduced. The time delay introduced by the computational time causes the stator current to oscillate around its reference. It also increases the current and torque ripples. To address this problem, a delay compensation method is adopted in this paper. Furthermore, the switching frequency of the inverter is significantly reduced by introducing the constraint of the power semiconductor switching number to the cost function of the MPDTC. Both simulation and experimental results are presented to verify the validity and feasibility of the proposed method.

• 한국항공우주학회지
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• 제38권1호
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• pp.35-41
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• 2010

최근의 항공기 개발에 있어 조종면을 복수 개로 분할하여 제어함으로써 예기치 못한 결함 발생 시 안전성 및 생존성을 향상 시킬 수 있는 재형상 제어에 관한 연구가 중요하게 대두되어 왔다. 본 논문은 조종면 결함 시 발생 가능한 조종면의 포화를 고려한 모델예측 제어기법을 이용한 재형상 제어를 다룬다. 모델예측 제어의 내부 모델로는 트림 조건에서 선형화된 운동방정식을 사용하며 조종면의 포화가 발생할 경우에 선형행렬부등식 기반의 반한정 프로그래밍을 이용한 최적화를 수행하며 그 외의 경우에는 모델예측 제어기법을 풀어서 구한 해석적인 해를 사용하는 제어기 구조를 제안한다. 제안된 알고리즘의 성능을 확인하기 위해 임의의 조종면 결함 상황에 대한 비선형 시뮬레이션을 수행하였다.

• 로봇학회논문지
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• 제19권1호
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• pp.8-15
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• 2024

This paper proposes a linear model predictive control of 6-DOF remotely operated underwater vehicles using nonlinear robust internal-loop compensator (NRIC). First, we design a integrator embedded linear model prediction controller for a linear nominal model, and then let the real model follow the values calculated through forward dynamics. This work is carried out through an NRIC and in this process, modeling errors and external disturbance are compensated. This concept is similar to disturbance observer-based control, but it has the difference that H_∞ optimality is guaranteed. Finally, tracking results at trajectory containing the velocity discontinuity point and the position tracking performance in the disturbance environment is confirmed through the comparative study with a traditional inverse dynamics PD controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.301-304
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• 1997

Two options arising during implementation of an advanced model-based control system on a process with low-level loops are discussed. Strengths and deficiencies of the options are examined and methods to overcome the deficiencies are proposed. Simulation results of a CSTR and distillation column are presented to demonstrate the performance improvements.

• International Journal of Air-Conditioning and Refrigeration
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• 제15권3호
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• pp.129-136
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• 2007

In this paper, we suggest PI control with the Smith predictive controller to improve transient response of a variable speed refrigeration system (VSRS). As the refrigeration system has long dead time inherently, it is difficult to get fast responses of super-heat and reference temperature. We incorporated the Smith predictive controller into PI to compensate the effect of the long dead time of the system. At first, we introduced the decoupling model of the system to control capacity and superheat simultaneously and independently. Next, we designed the predictive controller of the superheat based on PI control law. Finally, the control performance by the proposed method was investigated through some numerical simulations and experiments. The results of the simulations and experiments showed that the proposed PI control with the predictive controller could obtain acceptable transient behaviour for the system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.101.5-101
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• 2001

A linear input/output data-based predictive control with integral action is developed. The control input is obtained directly from the input/output data in a single step. However, the state estimation in subspace identification gives a biased estimate and there is model mismatch when the controller is applied to a nonlinear process. To overcome such difficulties, we add integral action to a linear input/output data-based predictive controller by augmenting the integrated white noise disturbance model and use each of best linear unbiased estimation(BLUE) filter and Kalman filter as a stochastic observer for the unmeasured disturbance. When applied to a continuous styrene polymerization reactor the proposed controller demonstrates.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.359-359
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• 2000

Generally, level control in the steam generator of a nuclear power plant is difficulty process control, because the low power operating can lead nonminimum phase characteristics(swell and shrink phenomenon) and flow measurement are unreliable and nonlinear characteristics. This paper presents a framework for solving this problem based on the constrained linear model predictive control and introduces the design of method for the level of the controller in the entire operating power of the steam generator, and compares with conventional PI controller.

• 제어로봇시스템학회논문지
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• 제6권4호
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• pp.254-260
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• 2000

This paper deals with the development of fault tolerant control for a nonlinear boiler system with noise and disturbance. The MCMBPC(Multivariable Constrained Model Based Predictive Control) is adopted for the control of the specific boiler turbin model. The fault detection and diagnosis are accomplished with the Kalman filter and two bias estimators. Once a fault is detected, two Bias estimators are driven to estimate the fault and to discriminate Process fault and sensor fault. In this paper, a fault tolerant control scheme combining MCMBPC with a fault compensation method based on the bias estimator is proposed. The proposed scheme has been applied to the nonlinear boiler system and shown a satisfactory performance through some simulations.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.272-283
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• 2017

In this paper, an improved predictive functional control (PFC) scheme for permanent magnet synchronous motor (PMSM) control system is proposed, on account of the standard PFC method cannot provides a satisfying disturbance rejection performance in the case of strong disturbances. The PFC-based method is first introduced in the control design of speed loop, since the good tracking and robustness properties of the PFC heavily depend on the accuracy of the internal model of the plant. However, in orthodox design of prediction model based control method, disturbances are not considered in the prediction model as well as the control design. A minimum-order observer (MOO) is introduced to estimate the disturbances, which structure is simple and can be realized at a low computational load. This paper adopted the MOO to observe the load torque, and the observations are then fed back into PFC model to rebuild it when considering the influence of perturbation. Therefore, an improved PFC strategy with torque compensation, called the PFC+MOO method, is presented. The validity of the proposed method was tested via simulation and experiments. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권2호
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• pp.65-75
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• 2004

This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.