• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.999-1004
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• 2005

An algorithm for a hybrid controller consists of a sliding mode control part and a fuzzy logic part which ar purposely for nonlinear systems. The sliding mode part of the solution is based on "eigenvalue/vector"-type controller is used as the backstepping approach for tracking errors. The fuzzy logic part is a Mamdani fuzzy model. This is designed by applying sliding mode control (SMC) method to the dynamic model. The main objective is to keep the update dynamics in a stable region by used SMC. After that the plant behavior is presented to train procedure of adaptive neuro-fuzzy inference systems (ANFIS). ANFIS architecture is determined and the relevant formulation for the approach is given. Using the error (e) and rate of error (de), occur due to the difference between the desired output value (yd) and the actual output value (y) of the system. A dynamic adaptation law is proposed and proved the particularly chosen form of the adaptation strategy. Subsequently VSC creates a sliding mode in the plant behavior while the parameters of the controller are also in a sliding mode (stable trainer). This study considers the ANFIS structure with first order Sugeno model containing nine rules. Bell shaped membership functions with product inference rule are used at the fuzzification level. Finally the Mamdani fuzzy logic which is depends on adaptive neuro-fuzzy inference systems structure designed. At the transferable stage from ANFIS to Mamdani fuzzy model is adjusted for the membership function of the input value (e, de) and the actual output value (y) of the system could be changed to trapezoidal and triangular functions through tuning the parameters of the membership functions and rules base. These help adjust the contributions of both fuzzy control and variable structure control to the entire control value. The application example, control of a mass-damper system is considered. The simulation has been done using MATLAB. Three cases of the controller will be considered: for backstepping sliding-mode controller, for hybrid controller, and for adaptive backstepping sliding-mode controller. A numerical example is simulated to verify the performances of the proposed control strategy, and the simulation results show that the controller designed is more effective than the adaptive backstepping sliding mode controller.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.3
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• pp.228-235
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• 2010

This paper deals with an autonomous flight controller design problem for a tilt-rotor aircraft in rotary-wing mode. The inner-loop algorithm is designed using the output-based approximate feedback linearization. The model error originated from the feedback linearization is cancelled within allowable tolerance by using single-hidden-layer neural network. According to Lyapunov direct stability theory, the adaptive update law is derived to run the neural network on-line, which is based on the linear observer dynamics. Moreover, the outer-loop algorithm is designed to track the trajectory generated from way-point guidance. Especially, heading and flight-path angle line-of-sight guidance are applied to the outer-loop to improve accuracy of the landing tracking performance. The 6-DOF nonlinear simulation shows that the overall performance of the flight control algorithm is satisfactory even though the collective input response shows instantaneous actuator saturation for a short time due to the lack of the neural network and the saturation protection logic in that loop.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.69-75
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• 2013

To increase the efficiency of the photovoltaic, almost photovoltaic appliances are controlled by Maximum Power Point Tracking(MPPT). Existing most of the PV MPPT techniques have used power which multiplies sensed output current and voltage of the solar cell. However, these algorithms are unnecessarily complicated and too expensive for small and compact system. The other hand, the proposed MPPT technique is only one sensing of the MPPT converter's output current, so there is no need to insert another sensors of battery side. Therefore, this algorithm is simpler compared to the traditional approach and is suitable for low power solar system. Further, the novel proper charge/discharge algorithm for the battery with PV MPPT is developed. In this algorithm, there is CC battery charge mode and load discharge mode of the PV cell & battery dual. Also we design current control to regulate allowable current during the battery charging. The proposed algorithm will be applicable to battery included solar cell applications like solar lantern and solar remote control car. Finally, the proposed method has been verified with computer simulation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.477-480
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• 2015

In this paper a low-voltage vibration energy harvesting circuit with MPPT(Maximum Power Point Tracking) control is proposed. By employing bulk-driven technique, the minimum operating voltage of the proposed circuit is as low as 0.8V. The designed MPPT control circuit traces the maximum power point by periodically sampling the open circuit voltage of a full-wave rectifier circuit connected to the piezoelectric device output and delivers the maximum available power to load. The proposed circuit is designed using a $0.35{\mu}m\;CMOS$ process, and the chip area including pads is $1.33mm{\times}1.31mm$. Simulation results show that the maximum power efficiency of the designed circuit is 85.49%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.412-415
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• 2015

This paper presents a MPPT(Maximum Power Point Tracking) control CMOS interface circuit for vibration energy harvesting. The proposed circuit consists of an AC-DC converter, MPPT Controller, DC-DC boost converter and PMU(Power Management Unit). The AC-DC converter rectifies the AC signals from vibration devices(PZT). MPPT controller is employed to harvest the maximum power from the PZT and increase efficiency of overall system. The DC-DC boost converter generates a boosted and regulated output at a predefined level and provides energy to load using PMU. A full-wave rectifier using active diodes is used as the AC-DC converter for high efficiency, and a schottky diode type DC-DC boost converter is used for a simple control circuitry. The proposed circuit has been designed in a 0.35um CMOS process. The chip area is $950um{\times}920um$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.201-208
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• 2017

Recently, the installation of photovoltaic(PV) systems has been increasing due to the worldwide interest in eco-friendly and abundant solar energy. On the other hand, a PV system has approximately 25% power loss while the energy generated from solar cells is transformed to the power coupling point through a power conversion system (DC/AC). If the output voltage of a string in the PV system is lower than the operating range of the inverter when a part of module in the string has a shadow due to weather conditions, the string is not synchronized and the whole efficiency of output power in a PV system may be reduced significantly. Therefore, to overcome this problem, this paper proposes a novel control method to compensate for the lower voltage by introducing a DC/DC voltage regulator for each string in a PV system, which adopts a concept for MPPT (Maximum Power Point Tracking) control function using the P&O algorithm and adopts constant voltage control method used in an existing inverter. This paper also implements a 2kW DC/DC voltage regulator based on the proposed algorithm and performs a variety of scenario-based experiments. From the simulation result, it was confirmed that the operation efficiency in the proposed method is improved compared to the existing method.

• Journal of the Korean Solar Energy Society
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• v.25 no.1
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• pp.1-10
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• 2005

In this paper, 150W photovoltaic system using neural network tracker is proposed, the system designed as the normal line of the solar cell always runs parallel the ray of the sun. This design can minimize the cosine loss of the system output results of solar cell are sensitive to the change of weather and insolation condition don't react rapidly to parameter condition change such as system circumstance and deterioration. To achieve precise operation of photovoltaic tracker system using method of intelligent control, Neural Network is used in the design of the photovoltaic tracker system drive. The control performance of this system drive influenced by the environment parameter such as weather condition and motor parameter variations. we used synchronous motor in this tracker and the experimental results show that the fixing system shows 10,159[Wh] and tracking system shows 12,360[Wh] electricity.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.520-523
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• 2004

A phase-locked loop control system designed by using the linear quadratic regulator approach is presented in this paper. The system thus designed is optimal system when system is in locked state and the parameter value of loop filter which is an active PI filter can be obtained easily. By considering the structure of loop filter of phase-locked loop is included in the process to be controlled, a type 1 servo system can be constructed when voltage control oscillator is considered as an integrator. The integral gain of the proposed system obtained by linear quadratic regulator approach can be used as an optimal value to design the parameter of loop filter. The implemented result in controlling the second-order lag pressure process by using the proposed scheme show that the system response is fast with no overshoot and no steady-state error. Furthermore, the experimental results are also shown in term of output disturbance effect rejection, tracking and process parameter changed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.518-526
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• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.822-826
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• 2013

In this paper, we propose an AFDO (Adaptive Fault Diagnosis Observer) and a fault tolerant controller for a class of nonlinear continuous-time system under the nonlinear abrupt actuator faults. Together with its estimation laws, the AFDO which estimates that the actuator faults is designed by using the Lyapunov analysis. Then, based on the designed AFDO, an adaptive sliding mode controller is proposed as the fault tolerant controller. Using Lyapunov stability analysis, we also prove the uniform boundedness of the state, the output and the fault estimation errors, and the asymptotic stability of the tracking error under the nonlinear time-varying faults. Finally, we illustrate the effectiveness of the proposed diagnosis method and the control scheme thorough computer simulations.