• 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.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.491-493
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• 2004

In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.7-12
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• 2012

In this paper, a direct controller for nonlinear plants using a neural network is presented. The controller is composed of an approximate controller and a neural network auxiliary controller. The approximate controller gives the rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not put too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network is trained and the system has a stable performance for the inputs it has been trained for. Simulation results show that it is very effective and can realize a satisfactory control of the nonlinear system.

• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1295-1301
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• 2010

In this note, a systematic general design of a new robust nonlinear variable structure controller based on state dependent nonlinear form is presented for the control of uncertain affine nonlinear systems with mismatched uncertainties and mismatched disturbance. After an affine uncertain nonlinear system is represented in the form of state dependent nonlinear system, a systematic design of a new robust nonlinear variable structure controller is presented. To be linear in the closed loop resultant dynamics, the nonlinear integral-type sliding surface is applied. A corresponding control input is proposed to satisfy the closed loop exponential stability and the existence condition of the sliding mode on the nonlinear integral-type sliding surface, which will be investigated in Theorem 1. Through a design example and simulation studies, the usefulness of the proposed controller is verified.

• 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.

• International Journal of Control, Automation, and Systems
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• v.3 no.spc2
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• pp.296-301
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• 2005

As a new control strategy, the Nonlinear PID (NLPID) controller has been introduced successfully in power systems. The controller is free of planting model groundwork during the design procedure and is therefore able to be achieved quite simply. In this paper, a nonlinear PID controller used for a superconducting magnetic energy storage (SMES) unit connected to a power system is proposed. The purpose of designing such a controller is to improve the stability of the power system in a relatively wide operation range. The design procedure takes into account the active and reactive power cooperative control scheme as well as the simple structure so as to be more apt to practical utilization. Simulation is carried out to investigate the performance of the proposed controller in a high order nonlinear power system model under the. MATLAB environment. The results show satisfactory performance and good robustness of the controller. The feasibility of the controller is testified as well.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.61-67
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• 2018

This paper presents a method to apply disturbance observer to PID controller for robustness enhancement of UAVs. The system uncertainties and disturbances bring adverse effects on performance and stability of UAVs. In this paper, we estimate the acceleration disturbances using nonlinear disturbance observer, then compensate disturbances with composite controller. By employing nonlinear disturbance observer and composite controller, we have better performance and robustness than conventional PID controller. The asymptotical stability of nonlinear disturbance observer is presented through theoretical analysis. The estimation performance of nonlinear disturbance observer is evaluated by numerical simulation. And performance of disturbance observer based PID controller is evaluated by comparing the performance with conventional PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.566-570
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• 2005

A digital controller for nonlinear time-delay system is proposed in this paper. A nonlinear time-delay system is discretized by using Taylor's discretization method. And the discretized system can be converted to a general nonlinear system. For this reason, general nonlinear controller synthesis can be applied to the discretized time-delay system. We adopted MAC controller synthesis for this study. Computer simulations are conducted to verify the performance of the proposed method. The results of simulation show good performance of the proposed controller synthesis and the proposed method is useful to control nonlinear time-delay system easily.