• Journal of Advanced Marine Engineering and Technology
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• v.36 no.7
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• pp.927-934
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• 2012

This paper suggests a new fuzzy PID controller with variable parameters which improves the shortage of the fuzzy PID controller with fixed parameters suggested in [9]. The derivation procedure follows the general design procedure of the fuzzy logic controller, while the resultant control law is the form of the conventional PID controller. Therefore, the suggested controller has two advantages. One is that it has only four fuzzy linguistic rules and analytical form of control laws so that the real-time control system can be implemented based on low-price microprocessors. The other is that the PID control action can always be achieved with time-varying PID controller gains only by adjusting the input and output scalers at each sampling time.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.9-15
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• 1999

A piezoelectric actuator is widely used in precision positioning applications due to its excellent positioning resolution. However, the piezoelectric actuator lacks in repeatability because of its inherently high hysteresis characteristic between voltage and displacement. In this paper, a controller is proposed to compensate the hysteresis nonlinearity. The controller is composed of a PID and a neural network part in parallel manner. The output of the PID controller is used to teach the neural network controller by the unsupervised learning method. In addition, the PID controller stabilizes the piezoelectric actuator in the beginning of the learning process, when the neural network controller is not learned. However, after the learning process the piezoelectric actuator is mainly controlled by the neural netwok controller. In this paper, the excellent tracking performance of the proposed controller was verified by experiments and was compared with the classical PID controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.7
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• pp.475-483
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• 1988

One of the advantages of the well-known PID controller is that it is a sufficiently flexible controller for many applications. But, when the plant parameters and disturbances are unknown or change with time, it is desirable to make automatic tuning of PID controller in order to achieve an acceptable level of performance of the control system. This paper presents a reformulation of the self-tuning pole-zero placement controller subject to some conditions and restrictions. It has the structure of a digital PID controller and is based on Vogel and Edgar's pole-zero placement design method. Various properties of this self-tuning PID controller are described and illustrated by simulation examples.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.85-89
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• 2004

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a neural network feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, hybrid control method of neural network controller and PID controller is presented. A neural network controller is operated as a main controller, a PID controller is a assistant controller which operates only when some undesirable phenomena occur, e.q., when the error hit the boundary of constraint set. The robust control function of neural network-PID hybrid controller is demonstrated by speed control of Motor.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.105-112
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• 2022

In this paper, unmanned underwater glider was designed for high-depth operation and adopted a bladder-type buoyancy controller for improving battery efficiency, and the motion controller controls the pitch angle by moving the internal mass battery. To improve the energy efficiency of the unmanned underwater glider, a layered PID controller that performs control by section was designed. Simulation program including 6-DOF motion equations and hydrodynamics coefficients of an unmanned underwater glider is constructed using Matlab/Simulink program. Control methods such as PID controller, sliding mode controller and layered PID controller were applied to the simulator to compare the dynamics performance and energy efficiency. As a result, the layered PID controller showed improved control performance compared to other controllers and improved energy efficiency of approximately 7.2% compared to PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.120-125
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• 2005

In this paper, We propose the fuzzy controller for the gain tuning of PID controller The proposed controller doesn't use the crisp output error and rule tables though with a fuzzy inference process in forward fuzzifier, New Fuzzy PID Controller assigns relations and ranges of two variables of PID gain parameters. These new gain parameters are calculated by the fuzzy inference with max-min ranges of Kp and Kd. The Ki parameter is computed automatically between Kp and Kd parameter Is calculated by Ziegler-Nickels tuning rules. Finally we experimented the propose controller by the hydraulic servo motor control system. We can obtained desired results through the good control characteristics.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.153-156
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• 1999

In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor membership function and control rules.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2006.06a
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• pp.77-78
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• 2006

A mixed method between $H_2\;and\;H_{\infty}$ control are widely applied to systems which has parameter perturbation and uncertain model to obtain an optimal robust controller. Brushless Direct Current (BLDC) motors are widely used for high performance control applications. Conventional PID controller only provides satisfactory performance for set-point regulation. However, with the presence of nonlinearities, uncertainties and perturbations in the system, conventional PID is not sufficient to achieve an optimal robust controller. This paper presents an approach to ease designing a Mixed $H_2/H_{\infty}$ PID controller for controlling speed of Brushless DC motors and the genetic algorithm is used to solve the optimized problems. Numerical results are shown to prove that the performance in the proposed controller is better than that in the optimal PID controller using LQR approach.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.1
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• pp.1-10
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• 2003

This paper is concerned with the fuzzy control scheme and PID controller for the vibration suppression control of a cantilever beam equipped with a laser sensor and an electromagnetic actuator. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriate PID gains in nonlinear systems and systems with time variant characteristic and so on. In this paper, we design the fuzzy based PID controller of which output gains are adjusted automatically and the designed controller is applied to active vibration control of a cantilever beam using electromagnetic actuator with strong nonlinearity. The tuning PID parameters of proposed controller are determined by using Fuzzy algorithm. Effectiveness and performance of the designed controller are verified by both simulation and experiment results. Experimental results demonstrate that better control performance can be achieved in comparison with the PID cotroller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.276-282
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• 2006

PID controller has been widely used in industry. Because it has a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and a robustness to system parameters variation and different velocity command. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.