• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.567-574
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• 2006

This paper presents the hardware implementation of a neural network controller for a nonlinear system with a micro-controller unit (MCU) and a field programmable gate array (FPGA) chip. As an on-line learning algorithm of a neural network, the reference compensation technique has been implemented on an MCU, while PID controllers with other functions such as counters and PWM generators are implemented on an FPGA chip. Interface between an MCU and a field programmable gate array (FPGA) chip has been developed to complete hardware implementation of a neural controller. The developed neural control hardware has been tested for balancing the inverted pendulum while controlling a desired trajectory of a cart as a nonlinear system.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.909-914
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• 1988

The structure of a digital controller based on modern control theory is more complex than that of a PID controller. In implementing the digital control of an actual system by using the digital controller, we often encounter gaps between theory and practice e.g. quantization error, sampling error, modeling error, contaminated noise etc. In such cases, simulator plays an important role in detecting difficulties. This paper demonstrates the importance of the computer simulator for designing a digital controller. The controller and the simulator are constructed by different computer respectively, with a link between the blocks by analogue signals through the A/D, D/A converters. Through the simulator test, we can evaluate the digital controller; identify and solve difficulties in the digital control. The controller, which pasted the simulator test, is used identically in the actual system. This was a successful procedure for designing the controller. As an example, we successfully constructed the digital controller using the computer simulator for inverted pendulum control. We then compared the control results of simulator and actual equipment. Furthermore we commented on the construction of the computer simulator which exactly expressed the actual system.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.506-508
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• 1998

In this paper, the optimal digital redesign is studied within the framework of fuzzy systems and dual-rate sampling control theory. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the optimal feedback gains developed in the continuous-time system, the constructed fuzzy system is converted into a continuous-time system. The developed continuous-time control law is converted into an equivalent slow-rate digital control law using the proposed digital redesign method. The digital redesign technique using a fuzzy model is employed to simulate the inverted pendulum dynamics.

• Journal of the Korea Computer Industry Society
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• v.2 no.7
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• pp.967-974
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• 2001

This paper aims at deriving an equivalent finite dimensional discrete-time system for $H{\infty}$ type problem for sampled-data control systems. A widely used approach is based on the lifting technique, but it needs somewhat complicate computation. Instead, this paper derives an equivalent finite-dimensional discrete-time system directly from a description of the sampled-data system which is achieved via a closed-loop expression of the worst-case intersample disturbance.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.510-512
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• 1999

In this paper, we present a method for the analysis and design of fuzzy controller for nonlinear systems. In the design procedure, we represent the dynamics of nonlinear systems using a Takagi-Sugeno fuzzy model and formulate the controller rules, which shares the same fuzzy sets with the fuzzy system, using parallel distributed compensation method. Then, after the feedback gain of each local state feedback controller is obtained using the existing optimal pole-placement scheme, we construct an overall fuzzy logic controller by blending all local state feedback controller. Finally, the effectiveness and feasibility of the proposed fuzzy-model-based controller design method has been evaluated through an inverted pendulum system.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.941-947
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• 2002

Two methods of constructing T-S fuzzy model which is equivalent to a given nonlinear system are presented. The first method is to obtain an equivalent T-S fuzzy model by using the sum of linearly independent scalar functions with constant real matrix coefficients. The sum of products of linearly independent scalar functions is used in the second method. The former method is to formulate the procedures of T-S fuzzy modeling dealt in many examples of previous publications; the latter is a new method. By comparing the number of linearly independent functions used in the two methods, we can easily find out which method makes fewer rules than the other. The nonlinear dynamics of an inverted Pendulum on a cart is used as an equivalent T-5 fuzzy modeling example.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.185-189
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• 2007

This paper deals with a fault detection system design for nonlinear systems with uncertain time varying parameters modelled as a T-S fuzzy system. A coprime factorization for T-S fuzzy systems is defined and a residual generator is designed using a left coprime factor. A fault detection criteria derived from the residual generator is also suggested. In order to demonstrate the efficacy of the suggested method, the fault defection method is applied to an inverted pendulum system and computer simulations are performed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.356-361
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• 2006

This paper deals with a fault detection system design for nonlinear systems with uncertain time varying parameters modelled as a T-S fuzzy system. A coprime factorization for T-S fuzzy systems is defined and a residual generator is designed using a left coprime factor. A fault detection criteria derived from the residual generator is also suggested. In order to demonstrate the efficacy of the suggested method, the fault detection method is applied to an inverted pendulum system and computer simulations are performed.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.621-629
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• 2007

In the adaptive fuzzy control field for affine nonlinear systems, there are two basic configurations: direct and indirect. It is well known that the direct configuration needs more restrictions on the control gain than the indirect configuration. In general, these restrictions are difficult to check in practice where mathematical models of plant are not available. In this paper, using a simple extension of the universal approximation theorem, we show that the only required constraint on the control gain is that its sign is known. The Lyapunov synthesis approach is used to guarantee the stability and convergence of the closed loop system. Finally, examples of an inverted pendulum and a magnet levitation system demonstrate the theoretical results.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.144-149
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• 1993

This paper discusses a design of a nonlinear control for a class of single-input double-output nonlinear mechanical systems. When conventional linearization methods are applied to the mechanical systems, some problems of oscillation and unstable phenomena arise. The proposed nonlinear control system resolves these problems. In this design the eigenvalues of the closed-loop nonlinear system are assigned to desired locations and local asymptotic stability of the closed-loop system. is guaranteed. The design method is applied to an inverted pendulum system with a moving weight mechanism. Experimental results show that the proposed nonlinear controller is more effective for stability than the usual linear controller.