• 한국정밀공학회지
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• 제29권1호
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• pp.79-86
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• 2012

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.632-634
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• 2000

The robust design of controllers to ensure gain and phase margin is can be use approximation of arctan function. In this paper, We proposed a tuning algorithm PID controllers based on specified gain and phase margin by a new approximation of arctan function. This method have linear interpolation equations of two arctan interval instead of one arctan interval of arctan(x). It is shown that the frequency response of this method was to ensure specified gain and phase margin.

• 한국정보전자통신기술학회논문지
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• 제6권4호
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• pp.243-248
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• 2013

In this thesis, we have designed the indirect adaptive controller using Dynamic Neural Units(DNU) for unknown nonlinear systems. Proposed indirect adaptive controller using Dynamic Neural Unit based upon the topology of a reverberating circuit in a neuronal pool of the central nervous system. In this thesis, we present a genetic DNU-control scheme for unknown nonlinear systems. Our method is different from those using supervised learning algorithms, such as the backpropagation (BP) algorithm, that needs training information in each step. The contributions of this thesis are the new approach to constructing neural network architecture and its training.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.227-230
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• 1998

In this paper, we propose the design method of fuzzy robust H$\infty$ controller for the uncertain nonlinear discete-time systems with time delay. First, we represent a nonlinear plant with a modified T-S(Takagi-Sugeno) fuzzy model. Then design method utilizing the concept of PDC (parallel distributed compensation) is employed. For the modified T-S fuzzy model with uncertainty and delay, the sufficient condition of the quadratic stabilization with an H$\infty$ norm bound is presented in terms of Lyapunov stability theory and fuzzy robust H$\infty$ controller design method is given by LMI(linear matrix inequality) approach. Also an illustrative example is given to demonstrate the result of the proposed method.

• 전자공학회논문지S
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• 제34S권1호
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• pp.43-53
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• 1997

A robust stability condition for linear systems with time delay in all variables and parameter uncertainties in all system matrices is derived. Robust performance condition that accounts for robust model-matching of closed loop system and disturbance rejection is also derived. Using the robust performance condition, robust $H^{\infty}$ controller and .mu.(sgructured singular value) controller with two-degree-of-freedom(2DOF) are designed. The controller structure is considered for $H^{\infty}$ controller, while uncertainity structure is considered for .mu. controller. Using the proposed method, $H^{\infty}$ and .mu. controllers for underwater vehicle with time delay and parameter variations are designed. Simulations of a design example with hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.ce.

• 대한전기학회논문지
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• 제36권7호
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• pp.484-491
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• 1987

A sufficent condition for the robust control of the adaptive control system is presented under the convergence of the parameters of the adaptive system. The plant in the adaptive control system is a stable system which includes the unmodelled dynamics and can be approximated by a minimum phase system. It is shown that modified structure which Kosut and Friedlander suggested satisfies the sufficient condition more easily than the original structure without modification. It is also shown by computer simulation that the modified structure and/ or the adaptation method using the normalized input and output data or filtered input and output data can improve the robustness of the adaptive control system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.761-763
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• 1999

When the controller designed by the $H{\infty}$ control technique is applied to the object system, sometimes the controller does not satisfy the robust stability and robust performance but only satisfy the nominal performance. In this paper, we derive the region on the frequency response curve of the open-loop transfer function which satisfy the robustness and robust performance of the designed controller. We also derive the region for the suitableness of the weighting function on the frequency response curve of the weighting function. We showed that the robust stability and the robust performance of the $H{\infty}$ optimal control)or by applying the designed controller on an electromechanical actuator system could be improved by determining parameter ${\gamma}$ and weighting function gain ${\alpha}$ using the derived region.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(5)
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• pp.17-20
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• 2002

This paper describes the synthesis of robust and non-fragile Η$^{\infty}$ output feedback controller for parameter uncertain systems with time delay. The sufficient condition of controller existence, and the design method of robust and non-fragile Η$^{\infty}$ output feedback controller are presented. The obtained conditions can be represented as parameterized LMIs, and PLMIs feasibility problems involve infinitely many LMIs hence are very hard to solve. Therefore, PLMIs are replaced by a finite set of LMIs using relaxation techniques(separated convexity concepts). This method is potentially conservative but often provide practically exploitable solutions of difficult problems with a reasonable computational effort. The compatibility of resulting controller is illustrated by numerical example.

• 전자공학회논문지S
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• 제34S권9호
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• pp.41-49
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• 1997

In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 추계학술대회 논문집
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• pp.306-312
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• 1996

The performance of the failure detection algorithm may be greatly influenced by the model uncertainty. It is very important to design a robust failure detection system to the model uncertainty. In this paper, a design procedure to generate failure detection algorithm is proposed. The design procedure suggested is based on the concept of the‘threshold selector［1］’. The H$\infty$ control algorithm is used to derive a threshold selector which is robust to the model uncertainty, The threshold selector derived can be used to develop a failure detection system together with the weighted cumulative sum algorithm［3］. Computer simulation study showed that the failure detection system designed for an ISA(Integrated Servo Actuator) system by using the proposed method is robust to the model uncertainty.