• 전자공학회논문지
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• 제50권8호
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• pp.245-249
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• 2013

In this paper, we propose two rate control algorithms for multi-view extension of HEVC with two rate control algorithms adopted in HEVC and analyze the multi-view rate control performance. The proposed multi-view rate controls are designed on HEVC-based multi-view video coding (MV-HEVC) platform with consideration of high-level syntax, inter-view prediction, etc. not only for the base view but also for the extended views using the rate control algorithms based on URQ (Unified Rate-Quantization) and R-lambda model adopted in HEVC. The proposed multi-view rate controls also contain view-wise target bit allocation for providing the compatibility to the base view. By allocating the target bitrates for each view, the proposed multi-view rate control based on URQ model achieved about 1.83% of average bitrate accuracy and 1.73dB of average PSNR degradation. In addition, about 2.97% of average bitrate accuracy and 0.31dB of average PSNR degradation are achieved with the proposed multi-view rate control based on R-lambda model.

• 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.

• 한국전자통신학회논문지
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• 제16권1호
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• pp.95-100
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• 2021

본 논문에서는 수중 건설 로봇을 제어하기 위한 모델 기반 메타 강화 학습 방법을 제안한다. 모델 기반 메타 강화 학습은 실제 응용 프로그램의 최근 경험을 사용하여 모델을 빠르게 업데이트한다. 다음으로, 대상 위치에 도달하기 위해 매니퓰레이터의 제어 입력을 계산하는 모델 예측 제어로 모델을 전송한다. MuJoCo 및 Gazebo를 사용하여 모델 기반 메타 강화 학습을 위한 시뮬레이션 환경을 구축하였으며 수중 건설 로봇의 실제 제어 환경에서의 모델 불확실성을 포함하여 제안한 방법을 검증하였다.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.1109-1114
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• 2022

The SMART (System-integrated Modular Advanced ReacTor) is an integral-type small modular reactor developed by KAERI (Korea Atomic Energy Research Institute). This paper discusses the feasibility and applicability of a 3D-based equivalent model using dynamic condensation method for seismic analysis of a SMART control rod drive mechanism. The equivalent model is utilized for complicated seismic analysis during the design of the SMART. While the 1D-based beam-mass equivalent model is widely used in the nuclear industry for its calculation efficiency, the 3D-based equivalent model is suggested for the seismic analysis of SMART to enhance the analysis accuracy of the 1D-based equivalent model while maintaining its analysis efficiency. To verify the suggested model, acceleration response spectra from seismic analysis based on the 3D-based equivalent model are compared to those from the 1D-based beam-mass equivalent model and experiments. The accuracy and efficiency of the dynamic condensation method are investigated by comparison to analysis results based on the conventional modeling methodology used for seismic analysis.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• 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.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권10호
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• pp.457-463
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• 2001

This paper presents a simple and new digital redesign algorithm for fuzzy-model-based controllers. In the first stage, a continuous-time TS fuzzy model is constructed for a given continuous-time nonlinear system and a corresponding continuous-time fuzzy-model-based controller is established based on the existing controller synthesis algorithms. In the second stage, the continuous-time fuzzy-model-based controller is converted to equivalent discrete-time fuzzy-model-based controller, aiming at maintaining the property of the analogue controlled system, which are called intelligent digital redesign. Finally, the proposed method is applied to the digital control of inverted pendulum system to shows the effectiveness and the effectiveness and the feasibility of the method.

• 제어로봇시스템학회논문지
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• 제5권2호
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• pp.166-173
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• 1999

Reference models are used in many control algorithms for improvement of transient response characteristics. They provide desired trajectories that the plant should follow Most control systems have bounded control inputs to avoid saturation of the plant. If we design the reference models that do not account for limits of the control inputs, control performance of the system may be deteriorated. In this paper a new approach of avoiding saturation by varying the reference model for TDC(time delay control) based systems subject to step changes in the reference input. In this scheme, the variable reference model is determined based on the information on control inputs and the size of the step changes in the reference inputs. This scheme was verified by application to the BLDC motor position control system in simulations and experiments. The responses of the TDC with the variable reference model showed better tracking performance than that with the fixed reference model.

• 한국자동차공학회논문집
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• 제18권3호
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• pp.26-36
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• 2010

This paper provides a description of the combustion model to obtain an accurate dynamic engine phenomena that satisfies real-time simulation for model-based engine control. The combustion chamber is modeled as a storage device for mass and energy. The combustion process is modeled in terms of a two-zone model for the burned and unburned gas fractions. The mass fraction burnt is modeled in terms of a Wiebe function. The instantaneous net engine torque is calculated from the engine speed and the instantaneous piston work. The modeling accuracy has been tested with a cylinder pressure data on a test bench and also the ability of real-time simulation has been checked. The results show that combustion model yields sufficiently good performance for the model-based control logic design. However the influence factors effected on model accuracy are some room for improvement.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.72-81
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• 2009

This paper presents a robust adaptive control method using model reference control strategy against autonomous robot systems with random friction nature. We approximate a nonlinear robot system model by means of a feedback linearization approach to derive nominal control law. We construct a Least Square (LS) based observer to estimate friction dynamics online and then represent a perturbed system model with respect to approximation error between an actual friction and its estimation. Model reference based control design is achieved to implement an auxiliary control in order for reducing control error in practice due to system perturbation. Additionally, we conduct theoretical study to demonstrate stability of the perturbed system model through Lyapunov theory. Numerical simulation is carried out for evaluating the proposed control methodology and demonstrating its superiority by comparing it to a traditional nominal control method.