• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.957-966
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• 2023

In this paper, we propose a new real-time adaptive PID temperature control technique. This is a technique that prevents overshoot by introducing a model that represents the control object. To prevent excessive integration that causes overshoot, integral control adjusts the integral gain to track the heat loss of the model in real time. In the conventional PID control, the integration was dependent on proportional control and the gain was fixed to a constant. As a result, applying two gains that mismatch each other could cause excessive overshoot. However, the proposed adaptive control actively eliminates overshoot so that the integral control amount does not always exceed the heat loss. The cause of overshoot in PID control is integration. Basically, proportional control does not cause overshoot. Therefore, according to the proposed technique, adaptive PID control without the need for tuning experiments can be realized.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.69-77
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• 1993

Adaptive Control is applied to regulate cutting force in turning operation under varying cutting conditions. Regulation is achieved primarily by adjusting feedrate. Such control leads to better machine utilization and increased tool life. The modeling of adaptive control system in turning operation is presented. The experimental results show that the adaptive PI controller is stable and performs more effective force control over wide range of cutting conditions as compared with the fixed gain PI controller.

• Steel and Composite Structures
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• v.46 no.1
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• pp.107-114
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• 2023

A new intelligent adaptive control scheme was proposed that combines observer disturbance-based adaptive control and fuzzy adaptive control for a composite structure with a mass-adjustable damper. The most important advantage is that the control structures do not need to know the uncertainty limits and the interference effect is eliminated. Three adjustable parameters in LMI are used to control the gain of the 2D fuzzy control. Binary performance indices with weighted matrices are constructed to separately evaluate validation and training performance using the revalidation learning function. Determining the appropriate weight matrix balances control and learning efficiency and prevents large gains in control. It is proved that the stability of the control system can be ensured by a linear matrix theory of equality based on Lyapunov's theory. Simulation results show that the multilevel simulation approach combines accuracy with high computational efficiency. The M-TMD system, by slightly reducing critical joint load amplitudes, can significantly improve the overall response of an uncontrolled structure.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.2
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• pp.179-189
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• 2011

In this paper, robust adaptive control design problem is addressed for a class of parametrically uncertain aeroelastic systems. A full-state robust adaptive controller was designed to suppress aeroelastic vibrations of a nonlinear wing section. The design used leading and trailing edge control actuations. The full state feedback (FSFB) control yielded a global uniformly ultimately bounded result for two-axis vibration suppression. The pitching and plunging displacements were measurable; however, the pitching and plunging rates were not measurable. Thus, a high gain observer was used to modify the FSFB control design to become an output feedback (OFB) design while the stability analysis for the OFB control law was presented. Simulation results demonstrate the efficacy of the multi-input multi-output control toward suppressing aeroelastic vibrations and limit cycle oscillations occurring in pre- and post-flutter velocity regimes.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.813-821
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• 2000

In this paper, we developed modeling of tension and speed dynamics for a two-drum winder in a three span continuous web transport system which had not been previously. Dynamic modeling of the time-varying nonlinear system was derived by considering the effect of the radii and mass moment of inertia in the unwinder and the two-drum winder through winding up the web. After linearizing it, we designed with a variable-gain a PID controller for tension control and a PI controller for speed. Simulation is carried out with the variation of radii and moment of inertia at high speed for the proposed tension control system with the two-drum winder and the variavle-gain a PID controller. Results show good performance of tension control during the speed change speed at a start-up and stop.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.480-483
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• 2003

This paper deals with speed control of Sensorless DC servo motor using a FTHGO(FuzEy-Tuning High Gain observer). In this paper, we improved the problem from row speed section, the problem of sensor for detecting speed of motor, using FTHGO(Fuzzy-Tuning High-Gain Observer) with fuzzy control technique which is a class of adaptive control technique. In order to verify the performance of the FTHGO(Fuzzy-Tuning High Gain Observer) which is proposed in this paper, it is proved from the experiment to compare the case with a speed sensor to the case with FTHGO(Fuzzy-Tuning High Gain observer) in the speed control of DC servo motor.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1610-1617
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• 1988

In this paper, a robust discrete-time adaptive control with compensation is proposed for single-input single-output discrete-time plants which have unmodeled dynamics. The stability of the overall system is studied using the conic sector stability theorems when a normalized constant gain parameter adaptation algorithm and a properly chosen compensation are used. An illustrative exmple shows that this compensation can also increase the parameter adaptation speed. And a method of compensation using the adaptive observation is also discussed.

• 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.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.210-212
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• 2006

This paper presents Hybrid PI(HBPI) controller of IPMSM drive using fuzzy adaptive mechanism 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, HBPI controller proposes a new method based self tuning PI controller. HBPI 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.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.73-75
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• 1987

The paper proposes a class of discrete-time adaptive controller which may be applicable without sufficient a priori information. Against choices of the Information, GPC algorithm may seem to be more robust than any other methods reported, but it is the method based on Indirect approach. It is, therefore, reasonable to propose an algorithm via the zero-gain prediction, in which the control parameters are directly estimated and calculated.