• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.158-160
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• 2005

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTD plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller and furthermore. the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.117-127
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• 2007

Many real world control systems usually track several control objectives, simultaneously. At the moment, it is desirable to meet all specified goals using the controllers with simple structures like as proportional-integral (PI) and proportional-integral-derivative (PID) which are very useful in industry applications. Since in practice, these controllers are commonly tuned based on classical or trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specifications. This paper addresses a new method to bridge the gap between the power of optimal multiobjective control and PI/PID industrial controls. First the PI/PID control problem is reduced to a static output feedback control synthesis through the mixed $H_2/H_{\infty}$ control technique, and then the control parameters are easily carried out using an iterative linear matrix inequalities (ILMI) algorithm. Numerical examples on load-frequency control (LFC) and power system stabilizer (PSS) designs are given to illustrate the proposed methodology. The results are compared with genetic algorithm (GA) based multiobjective control and LMI based full order mixed $H_2/H_{\infty}$ control designs.

• International Journal of Ocean System Engineering
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• v.1 no.3
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• pp.120-135
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• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.20-23
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• 2006

This paper presents a new approach to the problem of designing a cascaded three-parameters controller for a given linear time invariant (LTI) plant in unity feedback system. We consider a proportional-integral-derivative (PID) and a first-order controller with the specified overshoot and settling time. This problem is difficult to solve because there may be no analytical solution due to the use of low-order controller. Furthermore, the zeros of controller just appear in the zeros of feedback system. The key idea of our method is to impose a constraint on the controller parameters so that the zeros of resulting controller are distant from the dominant pole of closed-loop system to the left as far as the given interval. Two methods realizing the idea are suggested. We have employed the characteristic ratio assignment (CRA) in order to deal with the time response specifications. It is noted that the proposed methods are accomplished only in parameter space. Several illustrative examples are given.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.47-56
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• 2005

This paper presents a performance improvement result with the aid of closed feedback controller loop to a micro gyroscope. The dynamic model of a micro gyroscope is derived and a conventional proportional and derivative controller is designed via frequency domain analysis. The proposed control loop is implemented using several analog devices and applied to the SNU-Bosch MEMS gyroscope to check its performance improvement in real environment. The experiments demonstrated the performance improvement with the proposed feedback control loop. The bandwidth, linearity, and bias stability are improved to 78 Hz, 0.504 %, and 0.043 deg/sec, respectively, from 35 Hz, 2.07 %, and 0.066 deg/sec of open loop system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.103-106
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• 1996

This paper presents an iterative fuzzy learning control scheme which is applicable to a broad class of nonlinear systems. The control scheme achieves system stability and boundedness by using the linear feedback plus adaptive fuzzy controller and achieves precise tracking by using the iterative learning rules. The switching mode control unit is added to the adaptive fuzzy controller in order to compensate for the error that has been inevitably introduced from the fuzzy approximation of the nonlinear part. It also obviates any supervisory control action in the adaptive fuzzy controller which normally requires high gain signal. The learning control algorithm obviates any output derivative terms which are vulnerable to noise.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1424-1429
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• 2003

In this paper, the design method of sliding mode control (SMC) system for SISO linear system is discussed. First, we consider the similarity between the design method of sliding mode hyper plane using the strict positive realness and the characteristics of zeros of feedback system and the design method of simple adaptive control. Based on such a consideration, we propose the new design method of SMC system using parallel dynamic compensator. As a result, SMC system can be constructed only with the derivative of output signal for controlled plant. The performance of SMC system designed by proposed method is confirmed through the numerical example.

• Journal of Convergence Society for SMB
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• v.4 no.1
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• pp.31-39
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• 2014

PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedback were changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control. We also applied to reference tracking problem with the designed auto-tuning scheme.

• Journal of KSNVE
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• v.7 no.1
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• pp.161-168
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• 1997

The present paper describes the vibration control experiment of composite plates with bonded piezoelectric sensor and actuator. The system is modeled as two degree-of-freedom system using modal coordinates and the system parameters are obtained from vibration tests. Kalman filter is adopted for extracting modal coordinates from sensor signal, and control algorithms applied to the system are Linear Quadratic Gaussian(LQG) control, Bang-Bang Control (BBC), Negative Velocity Feedback(NVF), Proportional Derivative Control(PDC). From observation of the spillover and control perfomance, it is concluded that a higher order control algorithm such as LQG rather than BBG, NVF, PDC is suitable for efficient simultaneous control of both bending and twisting modes of composite plates.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.886-891
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• 1987

In this paper, we present a effective method to control robotic systems by an iterative learning algorithm. This method is based on the concepts of the learning control law which is introduced in this paper, that is, avoidance of using derivative of system state and ignorance of high frequency influence in system performance. By means of the betterment of performance due to the improvement of estimated unknown information, the learning control algorithm compels the system to gradually approach in desired trajectory, and eventually the tracking error asymptotically converges upon zero. In order to verify its utility, one degree of freedom of manipulator has been used in the experiments and the results illustrate this control scheme is very effective.