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망각인자 기반 순환최소자승 기법을 이용한 감쇠 시스템의 적응형 모델 독립 제어 알고리즘 개발
오광석(Kwang Seok Oh) 대한기계학회 2018 大韓機械學會論文集A Vol.42 No.2
본 논문은 감쇠 시스템을 위한 망각인자 기반 순환최소자승 기법을 이용한 적응형 모델 독립 제어 알고리즘 개발에 관한 것이다. 현실에서 복잡하고 비선형적 특성을 보이는 대상 시스템을 제어하기 위해서는 선형화된 수학적 모델 없이는 합리적인 제어성능을 확보하기 어렵다. 하지만 대상 시스템의 특정 구간별 입력과 출력의 관계는 일반적으로 1계 시스템으로 근사화될 수 있기 때문에 본 연구에서 제안하는 적응형 모델 독립 제어 알고리즘은 입력과 출력을 이용하여 복잡하고 비선형적 특성을 보이는 대상 시스템을 1계 시스템으로 추정하는 방법을 사용한다. 추정된 1계 시스템의 불확실성은 시스템의 입력과 출력을 이용하는 외란관측기를 이용해 추정되었으며 제어 입력을 도출하는데 사용되었다. 제안된 제어 알고리즘의 성능평가를 위해 복잡하고 비선형 특성을 갖는 수학적 모델과 실제 모터 시스템을 이용하였다. 성능평가 결과 대상 시스템의 입력과 출력만을 이용하여 시스템의 출력을 합리적으로 제어하는 것을 확인할 수 있었다. This paper presents an adaptive model-free control algorithm for damped systems based on recursive least-squares with multiple forgetting. It is difficult to control a complex nonlinear system in the real world, for reasonable control performances, without proper mathematical model of the system. However, the input-output relationship in a specific data region of the system can be approximated as a first-order system. Therefore, the developed adaptive model-free control algorithm in this paper has been designed to estimate the objective complex nonlinear system as a first-order system using the input-output relationship. The uncertainty of the estimated first-order system based on input and output has been estimated using the disturbance observer method, and the estimated disturbance has been used for the computation of the control input. In order to evaluate the performance of the developed control algorithm, a complex nonlinear mathematical model and actual DC servo motor system were used. The results show that the developed adaptive model-free control algorithm in this paper can control the output of the system to track the desired output reasonably using only input and output information.
회전관성의 순환최소자승 추정을 이용한 모델 예견 기반 굴삭기의 충돌회피 알고리즘 개발
오광석(Kwang Seok Oh),서자호(Jaho Seo),이근호(Geun Ho Lee) 유공압건설기계학회 2016 드라이브·컨트롤 Vol.13 No.4
This paper proposes a model-prediction-based collision-avoidance algorithm for excavators for which the recursive-least-squares (RLS) estimation of the excavator’s rotational inertia is used. To estimate the rotational inertia of the excavator, the RLS estimation with multiple forgetting and two updating rules for the nominal parameter and the forgetting factors was conducted based on the excavator-swing dynamics. The average value of the estimated rotational inertia that is for the minimizing effects of the estimation error was computed using the recursive-average method with forgetting. Based on the swing dynamics, the computed average of the rotational inertia, the damping coefficient for braking, and the excavator’s braking angle were predicted, and the predicted braking angle was compared with the detected-object angle for a safety evaluation. The safety level defined in this study consists of the three levels safe, warning, and emergency braking. The analytical rotational-inertia-based performance evaluation of the designed estimation algorithm was conducted using a typical working scenario. The results of the safety evaluation show that the predictive safety-evaluation algorithm of the proposed model can evaluate the safety level of the excavator during its operation.
망각 순환 최소자승을 이용한 다축 전지형 크레인의 적응형 모델 독립 제어 기반 조향제어 알고리즘
오광석(Kwangseok Oh),서자호(Jaho Seo) 유공압건설기계학회 2017 드라이브·컨트롤 Vol.14 No.2
This paper presents the algorithm of an adaptive model-free-control-based steering control for multi-axle all-terrain cranes for which the recursive least squares with forgetting are applied. To optimally control the actual system in the real world, the linear or nonlinear mathematical model of the system should be given for the determination of the optimal control inputs; however, it is difficult to derive the mathematical model due to the actual system’s complexity and nonlinearity. To address this problem, the proposed adaptive model-free controller is used to control the steering angle of a multi-axle crane. The proposed model-free control algorithm uses only the input and output signals of the system to determine the optimal inputs. The recursive least-squares algorithm identifies first-order systems. The uncertainty between the identified system and the actual system was estimated based on the disturbance observer. The proposed control algorithm was used for the steering control of a multi-axle crane, where only the steering input and the desired yaw rate were employed, to track the reference path. The controller and performance evaluations were constructed and conducted in the Matlab/Simulink environment. The evaluation results show that the proposed adaptive model-free-control-based steering-control algorithm produces a sound path-tracking performance.
적응형 슬라이딩 모드 제어를 이용한 위상 궤적 해석 기반 굴삭기의 안전제어 알고리즘 개발
오광석(Kwang Seok Oh),서자호(Ja Ho Seo),이근호(Geun Ho Lee) 유공압건설기계학회 2018 드라이브·컨트롤 Vol.15 No.3
This paper presents a phase portrait analysis–based safety control algorithm for excavators, using adaptive sliding mode control. Since working postures and material types cause the excavator"s rotational inertia to vary, the rotational inertia was estimated, and this estimation was used to design an adaptive sliding mode controller for collision avoidance of the excavator. In order to estimate the rotational inertia, the recursive least-squares estimation with multiple forgetting was applied with the information of the swing velocity of the excavator. For realistic evaluation, an actual working scenario–based performance evaluation was conducted. Based on the estimated rotational inertia and an analysis of estimation errors, sliding mode control inputs were computed. The actual working scenario–based performance evaluation of the designed safety algorithm was conducted, and the results showed that the developed safety control algorithm can efficiently avoid a collision with an object in consideration of rotational inertia variations.
다중 재귀 최소 자승 추정 알고리즘 기반 모빌리티의 회전체 건전성 모니터링 방법 개발
라한별,이지웅,오광석 사단법인 한국자동차안전학회 2024 자동차안전학회지 Vol.16 No.2
This study presents a method for health monitoring of rotating objects for mobility based on multiple recursive least squares(RLS) algorithms. The performance degradation of the rotating objects causes low handing / low driving performances and even fatal accidents. Therefore, health monitoring algorithm of rotating objects is one of the important technologies for mobility fail-safe and maintenance areas. In order for health monitoring of rotating objects, four recursive least squares algorithms with forgetting factor were designed in this study. The health monitoring algorithm proposed in this study consists of two steps such as uncertainty estimation and parameter changes estimation. In order to improve estimation accuracy, time delay function was applied to the estimated signals based on the first order differential equation and forgetting factors used for the RLS were reasonably tuned. The health monitoring algorithm was constructed in Matlab/Simulink environment and simulation-based performance evaluation was conducted using DC motor model. The evaluation results showed that the proposed algorithm estimates the actual parameter differences reasonably using velocity and current information.