• 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.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.552-563
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• 2005

In this paper, we propose a wavelet based fuzzy neural network (WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges the advantages of the neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of the wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of a mobile robot via the gradient descent (GD) method. In addition, an approach that uses adaptive learning rates for training of the WFNN controller is driven via a Lyapunov stability analysis to guarantee fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control results of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2254-2259
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• 2005

In this paper, we propose a wavelet based fuzzy neural network(WFNN) based direct adaptive control scheme for the solution of the tracking problem of mobile robots. To design a controller, we present a WFNN structure that merges advantages of neural network, fuzzy model and wavelet transform. The basic idea of our WFNN structure is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. In our control system, the control signals are directly obtained to minimize the difference between the reference track and the pose of mobile robot using the gradient descent(GD) method. In addition, an approach that uses adaptive learning rates for the training of WFNN controller is driven via a Lyapunov stability analysis to guarantee the fast convergence, that is, learning rates are adaptively determined to rapidly minimize the state errors of a mobile robot. Finally, to evaluate the performance of the proposed direct adaptive control system using the WFNN controller, we compare the control performance of the WFNN controller with those of the FNN, the WNN and the WFM controllers.

• 한국공작기계학회논문집
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• 제10권2호
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• 한국항공우주학회지
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• 제34권1호
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• pp.95-102
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• 2006

펄스형 플라즈마 전기추력기의 설계기술과 제어기법에 있어서는 과거의 기술에 비하여 많은 도약을 하였다. 그리고, 펄스형 플라즈마 전기추력기의 충전된 전기에너지는 추력기 구동시 중요한 비중을 차지함을 알 수 있다. 펄스형 플라즈마 전기추력기는 매 분사시 축전기에 충전된 전기에너지를 방전시켜 분사 시키므로서 추력을 얻는 장치이다. 따라서, 매 분사시 균일한 추력을 얻고자 할 경우에는 동작시점에서 균일한 전기 에너지가 충전되어 있어야 한다. 따라서, 본 논문에서는 매 분사시 균일한 추력을 얻기 위한 기법과 축전기와 추력기 엔진간의 기하학적 연결에 따른 안정성을 연구하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.92.1-92
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• 2001

Sliding mode control of spacecraft attitude tracking with actuator, especially reaction wheel, is presented. The sliding mode controller is derived based on quaternion parameterization for the kinematic equations of motion. The reaction wheel dynamic equations represented by wheel input voltage are presented. The input voltage to wheel is calculated from the sliding mode controller and reaction wheel dynamics. The global asymptotic stability is shown using a Lyapunov analysis. In addition the robustness analysis is taken for nonlinear system with parameter variations and disturbances. It is shown that the controller ensures control objectives for the spacecraft with reaction wheels.

• 호남수학학술지
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• 제30권2호
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• pp.369-378
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• 2008

Modeling nonlinear friction effects is a challenging problem. In this paper, a tracking controller is proposed for a system with uncertain nonlinear friction dynamics. Instead of using a specific friction model, we assume that the friction dynamics are represented by a function, which is unknown except its being continuously differentiable and Lipschitz continuous with known Lipschitz constants. It is shown that the scheme results in friction identification and trajectory position and velocity tracking. The analysis is done using Lyapunov-based stability method.

• 제어로봇시스템학회논문지
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• 제2권1호
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• pp.5-8
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• 1996

This paper proposea a new adaptive algorithm to improve the performance fo a robust adaptive control system. This adaptive algorithm counteracts the effects of disturbances and makes the time derivative of Lyapunov function non-positive, $V{\leq}0$. As a result, the output error approaches zero as $t\;\rightarrow\;\infty$ not only in the presence of bounded disturbances, but also in the ideal case. The effectiveness of this proposed algorithm is demonstrated by the stability analysis and simulation results.

• 한국통신학회논문지
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• 제17권12호
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• pp.1333-1342
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• 1992

본 논문은 제어 입력 u(t)에 대하여 비선형 결합된 3차 미분 방정식으로 표현되는 조작기를 갖는 로보트 매니퓰레이터에 대하여 제어기의 설계에 관한 논문이다. 제어 방식은 두 단계로 구성되며, 첫째 단계로는 비결합된 제어가능한 선형 계통을 얻기 위하여 대역적(global)선형화를 수행하며, 둘째 단계로는 선형화 계통에 대하여, 모델의 불확실성이 존재하는 경우에도 강건성과 안정도를 보장하도록 Lyapunov 방정식과 전체 안정도 이론을 적용하여 제어기를 설계한다. 제안된 제어기를 조작기가 포함된 자유도가 3인 로보트 매니퓰레이터에 대하여 컴퓨터 시뮬레이션을 하였다.

• 전기학회논문지
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• 제60권11호
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• pp.2139-2146
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• 2011

In this paper, a robust adaptive controller is proposed for trajectory tracking of robot manipulators with the unknown friction coefficient and bounded disturbance. A new adaptive control law is developed based on sliding mode and derived from the Lyapunov stability analysis. The introduction of a boundary layer solves the problem of chattering. The proposed adaptive controller is globally asymptotically stable and guarantees zero steady state error for joint positions. The estimated friction coefficients can also approach the actual coefficients asymptotically. A simulation example is provided to demonstrate the performance of the proposed algorithm.