• Journal of Power Electronics
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• 제19권4호
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• pp.989-999
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• 2019

This paper proposes a fault-tolerant control strategy with finite control set model predictive control (FCS-MPC) based on hierarchical optimization for five-level H-bridge neutral-point-clamped (5L-HNPC) inverter-fed induction motor drives. Fault-tolerant operation is analyzed, and the fault-tolerant control algorithm is improved. Adopting FCS-MPC based on hierarchical optimization, where the voltage is used as the controlled objective, called model predictive voltage control (MPVC), the postfault controller is simplified as a two layer control. The first layer is the voltage jump limit, and the second layer is the voltage following control, which adopts the optimal control strategy to ensure the current following performance and uniqueness of the optimal solution. Finally, simulation and experimental results verify that 5L-HNPC inverter-fed induction motor drives have strong fault tolerant capability and that the FCS-MPVC based on hierarchical optimization is feasible.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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• pp.421-424
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• 2008

The real time modeling of dynamic system on adaptive control system is very important for flying control system(FCS). Using traditional method, it is required much calculation load for integral/differential at control system. Therefore, It is very important theme of study in these days to find algorithms for integration/differential at FCS. These algorithms for integral/differential influence strongly stability/reliability to control flying object. In this paper, we present optimal predictive sampling time for reduce calculation load at FCS and optimal predictive time on general cost function by applying adaptive control method.

• 전력전자학회논문지
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• 제19권5호
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• pp.415-421
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• 2014

This study proposes a model-based predictive control for interleaved multi-phase DC/DC converters. The power values necessary to adjust the output voltage in the succeeding are predicted using a converter model. The output power is controlled by selecting the optimal duty cycle. The proposed method does not require controller loops and modulators for converter switching. This method can control the converter by calculating the optimal duty cycle, which minimizes the error between the reference and actual output voltage. The effectiveness of the proposed method is verified through simulations and experiments.

• 제어로봇시스템학회논문지
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• 제11권1호
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• pp.19-26
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• 2005

This paper is concerned with the design of a predictive PID controller which has similar features to the model-based predictive controller. A PID type control structure is defined, which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are precalculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with the conventional PID and fuzzy control algorithms.

• International Journal of Aeronautical and Space Sciences
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• 제12권1호
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• pp.16-23
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• 2011

In this paper, nonlinear model predictive control (NMPC) is addressed to develop formation guidance for multiple unmanned aerial vehicles. An NMPC algorithm predicts the behavior of a system over a receding time horizon, and the NMPC generates the optimal control commands for the horizon. The first input command is, then, applied to the system and this procedure repeats at each time step. The input constraint and state constraint for formation flight and inter-collision avoidance are considered in the proposed NMPC framework. The performance of NMPC for formation guidance critically degrades when there exists a communication failure. In order to address this problem, the modified optimal guidance law using only line-of-sight, relative distance, and own motion information is presented. If this information can be measured or estimated, the proposed formation guidance is sustainable with the communication failure. The performance of this approach is validated by numerical simulations.

• Journal of Power Electronics
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• 제19권1호
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• pp.168-178
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• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.

• 전자공학회논문지S
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• 제35S권7호
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• pp.22-28
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• 1998

This paper includes AC servo motor speed control usig the predictive control strategy. Generally, AC servo motor control should have the fast response characteristics. For the issue, sliding mode control and PID control have been applied. However, the former has the speed ripple response due to the chattering and the latter requires the many trial efforts. Originally, the predictive control which has been used in process control area does not need the priori knowledge for the application system and it is easy to compute the optimal gain with the prediction. In this paper, the TMS320C31 DSP pocessor is used for AC motor control with fst dynamics and the tuning guid-line for the parameters of the predictive control algorithm is given in order to reduce the computation load. Also, the actuator saturationis implemented uisngthe QP(Quadratic Programming) method and the transient response is improved by the identified intertia coefficient when AC motor is drived at forward/reverse rotation.

• Smart Structures and Systems
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• 제11권6호
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• pp.623-635
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• 2013

This paper investigates application of a control algorithm called model predictive sliding mode control (MPSMC) to active vibration suppression of a cantilevered aluminum beam. MPSMC is a relatively new control algorithm where model predictive control is employed to enhance sliding mode control by enforcing the system to reach the sliding surface in an optimal manner. In previous studies, it was shown that MPSMC can be applied to reduce hysteretic effects of piezoelectric actuators in dynamic displacement tracking applications. In the current study, a cantilevered beam with unknown mass distribution is selected as an experimental test bed in order to verify the robustness of MPSMC in active vibration control applications. Experimental results show that MPSMC can reduce vibration of an aluminum cantilevered beam at least by 29% regardless of modified mass distribution.

• Journal of Power Electronics
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• 제18권6호
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• pp.1771-1779
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• 2018

Modern trams with a super capacitor have gained a lot of attention in recent years due to its reliability, convenience, energy conservation and environmental friendliness. Because of its special charging characteristic, the traditional charging structure and control strategy cannot satisfy its charging requirements. This paper presents a new charging topology for fast charging modern trams with a super capacitor and it designs a controller using continuous control set model predictive control (CCS-MPC). There are three contributions in this paper. First, a new charging structure is designed and its mathematics model is derived. The cascade structure is adopted instead of the parallel structure to simplify the control process and to keep the rated power of the controllable part low. Second, a MPC control strategy is proposed to satisfy the charging characteristic. The optimal control signal can be obtained by solving the designed optimization problem. The optimal control signal is related to the discrete control action. In addition, mapping between the continuous control signal and the discrete control action is designed. Third, a semi-physical experimental platform is built to verify the proposed topology and control method. The simulation model and experiment platform are built to verify the correctness of the new structure and its control method. The results obtained show that the new topology can work effectively.

• 설비공학논문집
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• 제12권7호
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• pp.680-687
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• 2000

The objective of this study is to improve the control performance of Ondol system which causes overheating and underheating with 2-position on/off control. For this, a predictive control that determines the suitable on/off positions using Artificial Neural Network(ANN) model was proposed Dynamic analyses using computer simulation show that the neural network used in the predictive control is adapted to each room whose loads variation and thermal characteristics are different. To examine the applicability of this predictive control with ANN it was compared with 2-position on/off control through experiments.