• 한국지능시스템학회논문지
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• 제26권1호
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• pp.16-22
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• 2016

세계적으로 수많은 로봇연구실에서 이륜 도립진자 이동로봇에 대한 연구가 진행되고 있다. 본 논문에서는 이런 이륜 도립진자 이동로봇이 평탄한 경사면에서 안정적으로 주행할 수 있도록 하는 강인 제어기를 개발하는 것으로 고려한다. 경사면에서 이륜 도립진자 이동로봇의 균형을 위해 3 자유도의 운동방정식에서 선회운동을 제한한 2 자유도 동력학식을 사용하며, 가변구조시스템 이론을 근간으로 하는 슬라이딩 모드 제어기를 제안하고 LQR 이론을 이용하여 슬라이딩 운동이 일어나는 슬라이딩 평면을 설계한다. 시뮬레이션을 위해 Mathworks사의 Simulink를 활용하여 이륜 도립진자 이동로봇의 2 자유도 모델을 실현하고, 슬라이딩 모드 제어기 또한 Simulink를 이용하여 구현한다. 시뮬레이션 결과를 통해 제안된 제어기가 경사면을 주행하는 이륜 도립진자 이동로봇을 효과적인 제어한다는 것을 보인다.

• 조명전기설비학회논문지
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• 제23권11호
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.77.2-77
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• 2002

Human upright standing posture in the sagittal plane is studied, when it exposed in the antero-posterior vibration. A two link inverted pendulum model is considered and described its functional behavior in terms of ankle and hip joint according to the dominant joints that provides the largest contribution to the corresponding human reactionary motion. The data is analyzed, both in the time domain and the frequency domain. Subjects behave as a non-rigid pendulum with a mass and a spring throughout the whole period of the platform motion. When vision was allowed, each segment of body shows more stabilized.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.468-471
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• 1994

This paper presents the digital implementation of an optimal and robust VSS controller with sliding observer. Firstly, a discrete-time VSS control law which enables the system state to move into a sliding sector where the closed-loop system is stable is designed. Then optimal control theory is used to design an optimal sliding sector. Secondly, a sliding observer which provide robust state estimation against model-plant mismatches due to parameter uncertainties is designed for the sampled-data multivariable systems. Finally, modified sliding observer which effectively reduce chattering of state variables in state estimation was proposed. The proposed scheme was applied 10 a two degree of freedom inverted pendulum with passive joint to verify robust motion control. Computer simulation results confirm the viability of the proposed observer-based controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.416-419
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• 2001

In this paper a new approach to estimate scaling factors of fuzzy controllers such as the fuzzy PID controller and the fuzzy PD controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors[1]. The desist procedure dwells on the use of evolutionary computing(a genetic algorithm) and estimation algorithm for dynamic systems (the inverted pendulum). The tuning of the scaling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as Neuro-Fuzzy model, and regression polynomial [7]. This method can be applied to the nonlinear system as the inverted pendulum. Numerical studies are presented and a detailed comparative analysis is also included.

• 제어로봇시스템학회논문지
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• 제19권9호
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• pp.834-838
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• 2013

This paper proposes a new ball robot which has a four axis structure and four motors that directly actuate the ball to move or to maintain the balance of the robot. For the Balancing control, it is possible to use non-model-based controller to control simply without complex formula. All the gains of the controller are heuristically adjusted during the experiments. The tilt angle is measured by IMU sensors, which is used to generate the control input of the roll and pitch controller to make the tilt angle zero. The performance of the designed control system has been verified through the real experiments with the developed ball robot.

• 전자공학회논문지S
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• 제35S권1호
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• pp.60-67
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• 1998

In this paper, a gain scheduling method of PID controller is proposed using fuzzy logic for balancing control of an inverted pendulum. First, gains of PID controller are calculated using pole-placement technique for the linearized model of an inverted pendulum and these gains are modified by fuzzy logic throughout control operations. A PD controller is used by switching near the set-point to improve the performance. It is illustrated by simulations that the proposed hybrid fuzzy control method yidels smaller rising time and overshoot compared to the fixed-gain PID controller or fuzzy logic-based only PID controller.

• 한국통신학회논문지
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• 제23권9A호
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• pp.2211-2220
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• 1998

This paper presetns an adaptive critic self-learning control system with cerebellar model articulation controller (CMAC)-based decoder integrated with the associative search element (ASE) and adatpive critic element(ACE)- based scheme. The tast of the system is to balance a pole that is hinged to a movable cart by applying forces to the cart's base. The problem is that error feedback information is limited. This problem can be sloved when some adaptive control devices are involved. The ASE incorporates prediction information for reinforrcement from a critic to produce evaluative information for the plant. The CMAC-based decoder interprets one state to a set of patways into the ASE/ACE. These signals correspond to te current state and its possible preceding action states. The CMAC's information interpolation improves the learning speed. And design inverted pendulum hardware system to show control capability with neural network.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권4호
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• pp.271-276
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• 2006

To implement a generalization of value functions in Adaptive Search Element (ASE)-reinforcement learning, CMAC (Cerebellar Model Articulation Controller) is integrated into ASE controller. ASE-reinforcement learning scheme is briefly studied to discuss how CMAC is integrated into ASE controller. Neighbourhood Sequential Training for CMAC is utilized to establish the look-up table and to produce discrete control outputs. In computer simulation, an ASE controller and a couple of ASE-CMAC neural network are trained to balance the inverted pendulum on a cart. The number of trials until the controllers are established and the learning performance of the controllers are evaluated to find that generalization ability of the CMAC improves the speed of the ASE-reinforcement learning enough to realize the cartpole control system.