• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.689-693
• /
• 1996

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.1129-1134
• /
• 1989

In this paper, we propose a neural network for learning to control semi-linear dynamical systems. The network is a composite system of four three-layer backpropagation subnetworks, and is able to control inverted pendulums better than systems based on modern control theory at least in some ranges of parameters. Three of the four subnetworks in our network system process angles, velocities, and positions of a moving inverted pendulum, respectively. The outputs from those three subnetworks are input to the remaining subnetwork that makes control decisions. Each of the four subnetworks learns connection weights independently by backpropagation algorithms. Teaching signals are given by the human operator. Also, input signals are generated by the human operator, but they are converted by preprocessors to actual input data for the three subnetworks except for the network for control decisions. The whole system is implemented on both of 16 bit personal computers and 32 bit workstations. First, we briefly provide the research background and the inverted pendulum problem itself, followed by the description of our composite neural network model. Next, some results from the simulation are given, which are subsequently compared with the results from a control system based on modern control theory. Then, some discussions and conclusion follow.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.04a
• /
• pp.164-167
• /
• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2170-2172
• /
• 2003

This paper presents the position tracking control of an inverted pendulum on an inclined railway. In general, inclining the railway leads to errors in the pendulum angle even though the pendulum is stabilized, which results in errors in the cart position. To solve this problem, a linear quadratic regulation (LQR) controller with an integrator is used for compensating the resulting error in the cart position. The proposed method is evaluated by comparing LQR controllers with and without an integrator. Experimental results show that the LQR controller with an integrator is better in performance than one without an integrator.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1262-1266
• /
• 2003

Fuzzy sliding mode controller for a class of uncertain nonlinear dynamical systems is proposed and analyzed. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10b
• /
• pp.1833-1838
• /
• 1991

This paper presents a stabilization technique for unstable systems. An inverted pendulum, which is a typical unstable mechanical system, is considered and stabilized by a nonlinear control. The stabilization problem in this system is related to that in postural control of human being. In this paper, the variable structure control (VSC) is applied to the stabilization problem. Robustness by the VSC and that by a conventional linear feedback controller are compared.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.963-965
• /
• 1999

A linear chromosome combined with a grid-based representation of the network and a new crossover operator allow the evolution of the architecture and the weights simultaneously. In our approach there is no need for a separate weight optimization procedure and networks with more than one type of activation function can be evolved. In this paper one evolutionary' strategy of a given dual neural controller was introduced and the simulation results were described in detail through applications to a stabilization control of an Inverted Pendulum System.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.878-883
• /
• 1991

In this paper, we propose the fuzzy-neural controller which is fuzzy controller with learning ability of neural network. The neural network in this controller is same as the membership function in current fuzzy controller and a parts of inference rules. And, it can be easily extend the control algorithm to multivariable systems. We can show effectiveness of the control algorithm through experiment of the inverted pendulum system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 1995.04a
• /
• pp.142-146
• /
• 1995

In the paper, Fuzzy Logic Controller(FLC) that determines its optimal coefficients using Genetic Algorithms is considered. It is also applied to the inverted pendulum problem known popularly as a standard plant. Flexibility of the inverted pendulum has been taken into account. In the results, Fuzzy Logic Controller under consideration successfully controls both rigid mode and flexible mode. The rule base of Fuzzy Logic Controller is automatically tuned using not only trial-error method but also Genetic Algorithms.

• Proceedings of the KIEE Conference
• /
• 1997.07b
• /
• pp.428-430
• /
• 1997

An LQG/LTR based gain scheduling control scheme for the two link inverted pendulum is presented. It is shown by simulation that the gain scheduling scheme based on the robust linear control theory still preserves the robust property of the linear control scheme and can be applied to control a class of nonlinear systems.