• Journal of Institute of Control, Robotics and Systems
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• v.13 no.3
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• pp.192-197
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• 2007

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1539-1544
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• 2005

The gauge control of the fishing mill is very important because more and more accurately sized hot rolled coils are demanded by customers recently. Because the mill constant and the plasticity coefficient vary with the specifications of the mill, the classification of steel, the strip width, the strip thickness and the slab temperature, the variation of these parameters should be considered in the automatic gauge control system(AGC). Generally, the AGC gain is used to minimize the effect of the uncertain parameters. In a practical field, operators set the AGC gain as a constant value calculated by FSU (Finishing-mill Set-Up model) and it is not changed during the operating time. In this paper, the thickness data signals that occupy different frequency bands are respectively extracted by adaptive filters and then the main cause of the thickness variation is analyzed. Additionally, the AGC gain is adaptively tuned to reduce this variation using the online tuning model. Especially ANFIS(Adaptive-Neuro-based Fuzzy Interface System) which unifies both fuzzy logics and neural networks, is used for this gain adjustment system because fuzzy logics use the professionals' experiences about the uncertainty and the nonlinearity of the system. Simulation is performed by using POSCO's data and the results show that proposed on-line gain adjustment algorithm has a good performance.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2123-2125
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• 2001

In thermal power plant, the efficiency of a combined power plant with a gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a separated 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul. Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired, and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controller.

• Journal of Advanced Navigation Technology
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• v.19 no.6
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• pp.473-483
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• 2015

This paper reports the single-input-single-output cascade control by using 1-axis attitude control test-bench for quad-rotor UAV. The test-bench was designed as a see-saw shape using 2 motors and propellers, and to enable changing the center of gravity with the center of gyration using ballast. The experiment was carried out by constructing a PID-PID controller having a cascade structure with the test-bench. The SIMC based PID gain tuning process, which makes PID gain tuning easy, was grafted to cascade control. To graft SIMC method, the system parameter estimation result was conducted with second order time delay model by using Matlab-Simulink. Gain tuning was conducted by simulating with estimated system parameter. In this paper, the conventional application of SIMC was conducted and improved application was proposed for improving stability at tuning process.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.160-168
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• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.

• Journal of Power Electronics
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• v.14 no.5
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• pp.980-988
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• 2014

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.96-106
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• 2001

As the drilling depth increases, the cutting torque increases and fluctuates, which can lead to the machine tool vibration, severe tool wear, and catastrophic tool breakage. Hence, cutting torque control is very important to improve productivity in drilling. In this paper, a PID controller was designed to control the drilling torque. The plant including the feed drive system, cutting process and spindle drive system was modeled for controller design. The Ziegler-Nichols method was used to determine the controller gain and control action times and the root locus plot was used to tune the controller gain for a certain cutting condition. Also, suggested was a simple method to obtain the tuned controller gain for an arbitrary cutting condition not using the Ziegler-Nichols method and the root locus plot. The performance of the designed controller and the effect of controller gain tuning were verified from experiments.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.260-262
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• 2006

This paper presents Hybrid-PI controller of induction motor drive using fuzzy control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, Hybrid-PI controller proposes a new method based self tuning PI controller. Hybrid-PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of induction motor are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.76-85
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• 1998

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.188-199
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• 2014

Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.