• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.134-141
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• 2003

PID controllers with constant gains have been widely used in various control systems due to its powerful performance and easy implementation. But it is difficult to have uniformly good control performance in all operating conditions. In this paper, we propose a nonlinear variable PR controller with immune feedback mechanism. An immune feedback mechanism is based on the functioning of biological T-cells, they include both an active term, which controls response speed. and an inhibitive term, which controls stabilization effect. Therefore, the proposed nonlinear PID controller is based on immune responses of biological. immune feedback mechanism which is the cell mediated immunity and In order to choose the optimal nonlinear PID controller games, we also propose the tuning algorithm of nonlinear function parameter in immune feedback mechanism. To verify performance of the proposed algorithm, the speed control of nonlinear DC motor are performed. Front the simulation results, we have found that the proposed algorithm is more superior to the conventional constant fain PID controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.259-267
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• 2003

In this paper, we propose a nonlinear variable PID controller using a cell-mediated immune response. An immune feedback response is based on the functioning of biological T-cells. An immune feedback response and P-controller of conventional PID controllers resemble each other in role and mechanism. Therefore, we extend immune feedback mechanism to nonlinear PE controller. And in order to choose the optimal nonlinear PID controller games, we also propose the on-line tuning algorithm of nonlinear functions parameters in immune feedback mechanism. The trained parameters of nonlinear functions are adapted to the variations of the system parameters and any command velocity. And the adapted parameters obtained outputs of nonlinear functions with an optimal control performance. To verify performances of the proposed control systems, the speed control of nonlinear BC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system variations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1319-1329
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• 2012

Globally stabilizing adaptive fuzzy state- and output-feedback controllers for the fully nonaffine pure-feedback nonlinear system are proposed in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis to be considerably simplified. For the global stabilty of the clossed-loop system, the self-structuring fuzzy system whose memebership functions and fuzzy rules are automatically generated and tuned is adopted. The proposed controllers employ only one fuzzy logic system to approximate unknown nonlinear function, which highlights the simplicity of the proposed adaptive fuzzy controller. Moreover, the output-feedback controller of the considered system proposed in this paper have not been dealt with in any literature yet.

• Journal of IKEEE
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• v.11 no.4
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• pp.213-218
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• 2007

We consider a web transport system. The objective of this paper is to design the output feedback controller such that the controller can track a desired tension and processing speed on web transport system. We propose the new design method using observer and feedback linearization technique. The proposed method use a nonlinear feedback to transform to linear system and high gain observer to estimate the state value. We show that the proposed controller can achieve the control object using only output. We show a performance of controller via the simulation.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.193-201
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• 1998

In this paper, the standard Dole, Glover, Khargoneker, and Francis (abbr. : DGKF 1989) H\ulcorner controller (H\ulcornerC) is extended to the nonlinear feedback linearization-H\ulcorner/sliding mode controller (NFL-H\ulcorner/SMC), to tackle the problem of the unmeasurable state variables as in the conventional SMC, to obtain smooth control as the linearized controller in a linear system, and to improve the time-domain performance under a worst scenario. The proposed controller is obtained by combining the H\ulcorner estimator with the nonlinear feedback linearization-sliding mode controller (NFL-SMC) and it does not need to measure all the state variables as in the traditional SMC. The proposed controller is applied as a nonlinear power system stabilizer (PSS) for the improvement of the power system damping characteristics of an single machine infinite bus system (SMIBS) connected through a double circuit line. The effectiveness of the proposed controller is verified by nonlinear time-domain simulation in case of a 3-cycle line-to-ground fault and in case of the parameter variations for the AVR gain K\ulcorner and for the inertia moment M.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.125-128
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• 2001

In this paper, We proposed the nonlinear controller and observer design for a ball and beam system. Unfortunately, for the ball and beam system, the control coefficient is zero whenever the angular velocity or ball position are zero. Therefore, the relative degree of the ball and beam system is not well defined. The presented the nonlinear controller and observer design is based on the approximation input-output feedback linearization. And we verified that the proposed nonlinear controller and observer scheme is the feasible through a computer simulation.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.184-192
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• 1998

In this paper, we present a nonlinear feedback linearization-full order observer/sliding mode controller (NFL-FOO/SMC), to obtain smmoth control as a linearized controller in a linear system (or to cancel the nonlinearity in a nonlinear system), and to solve the problem of the unmeasurable state variables as in the conventional SMC. The proposed controller is obtained by combining the nonlinear feedback linearization-sliding mode control (NFL-SMC) with the full order observer (FOO)and eliminates the need to measure all the state variables in the traditional SMC. The proposed controller is applied to the nonlinear power system stabilizer (PSS) for damping oscillations in a power system. The effectiveness of the proposed controller is verified by the nonlinear time-domain simulations in case of a 3-cycle line-to-ground fault and in case of the parameter variation for the AVR gain K\ulcorner and for the inertia moment M.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.851-856
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• 2011

In this paper, the fuzzy output-feedback controller is addressed for a discrete-time nonlinear interconnected systems with common input. The nonlinear interconnected system is represented by a T-S (Takagi-Sugeno) fuzzy model. Based on T-S fuzzy interconnected system, the fuzzy output-feedback controller is designed with common input. The stability condition of the closed-loop system is represented to the LMI (Linear Matrix Inequality) form. PEMFC model is given to show the verification of the controller discussed throughout the paper.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.494-499
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• 2013

Based on the state-feedback adaptive neuro-control algorithm for a SISO nonaffine pure-feedback nonlinear system proposed in [15], an output-feedback controller is proposed in this paper. The output-feedback adaptive neural-net controller for the considered nonlinear system has not been previously proposed in any other literatures yet. The proposed output-feedback controller inherits all the advantages of [15] such that it does not adopt backstepping and this results in relatively simple control and adapting laws. Only one neural network is required for the proposed adaptive controller. The proposed neural-net control scheme expands the applicable class of nonlinear systems.