• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.119-125
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• 1997

This paper deals with an experimental investigation on an active vibration control of ahybrid smart structure(HSS) via an electro-rheological fluid actuator(ERFA) and a piezoelectric film actuator(PFA). Firstly, an HSS is constructed by inserting a silicone oil-based electro-rheological fluid into a hollow can- tilevered beam and perfectly bonding piezoelectric films ofn the upper and lower surfaces of the beam as an actuator and a sensor, respectively. The control scheme of the ERFA tuning stiffness and damping charac- teristics of the HSS with imposed electric fields is formulated as a function of excitation frequencies on the basis of field-dependent respnses. On the other hand, as for the control scheme of the PFA permitting control voltages to generate axial forces or bending moments for suppressing deflections of the HSS, a neuro sliding mode controller(NSC) is employed. Furthermore, an experimental implementation activating the ERFA and the PFA independently is established to carry out an active vibration control in both the transient and forced vibrations. The experimental results exhibit a superior ability of the gtbrid actuation system to tailor elastodynamic response characteristics of the HSS rather than a single class of actuator system alone.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.650-652
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance. FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and increase efficiency, a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy Pi and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and them. The resultant rule base is Macvicar-Whelan type. The frequency response information is used in tuning of membership functions. Also a tuning strategy for the scaling factors is Proposed based on the relationship between PID gain and them. Simulation results show better performance and the effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.547-558
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• 2007

This paper proposes a simpler solution to the stabilization problem of a special class of nonlinear underactuated mechanical systems which includes widely studied benchmark systems like Inertia Wheel Pendulum, TORA and Acrobot. Complex internal dynamics and lack of exact feedback linearizibility of these systems makes design of control law a challenging task. Stabilization of these systems has been achieved using Energy Shaping and damping injection and Backstepping technique. Former results in hybrid or switching architectures that make stability analysis complicated whereas use of backstepping some times requires closed form explicit solutions of highly nonlinear equations resulting from partial feedback linearization. It also exhibits the phenomenon of explosions of terms resulting in a highly complicated control law. Exploiting recently introduced Dynamic Surface Control technique and using control Lyapunov function method, a novel nonlinear controller design is presented as a solution to these problems. The stability of the closed loop system is analyzed by exploiting its two-time scale nature and applying concepts from Singular Perturbation Theory. The design procedure is shown to be simpler and more intuitive than existing designs. Design has been applied to important benchmark systems belonging to the class demonstrating controller design simplicity. Advantages over conventional Energy Shaping and Backstepping controllers are analyzed theoretically and performance is verified using numerical simulations.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.67-77
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• 2004

In this paper, a new approach to the automation of the cultivation in a green house is suggested and a practical automatic control cultivation system is implemented. To automatically control and optimize the very nonlinear and time-varying growth of farm products, a hybrid strategy(FECA, Fuzzy Expertized Control Algorithm) is proposed which serially combines a fuzzy expert system with the fuzzy logic control. The fuzzy expert system(FMES, Fuzzy Model-based Expert System is intended to overcome the non-linearity of the growth of farm products. The part of fuzzy controller(FLC, Fuzzy Logic Controller) is incorporated to solve the time-variance of the growth of farm products. Finally, the efficiency and the effectiveness of the implemented agricultural automation system is presented through the cultivation results.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1293-1302
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• 1999

In this paper, an on-line process scheme is presented for implementation of a intelligent on-line modeling of nonlinear complex system. The proposed on-line process scheme is composed of FNN-based model algorithm and PLC-based simulator, Here, an adaptive fuzzy-neural networks and HCM(Hard C-Means) clustering method are used as an intelligent identification algorithm for on-line modeling. The adaptive fuzzy-neural networks consists of two distinct modifiable sturctures such as the premise and the consequence part. The parameters of two structures are adapted by a combined hybrid learning algorithm of gradient decent method and least square method. Also we design an interface S/W between PLC(Proguammable Logic Controller) and main PC computer, and construct a monitoring and control simulator for real process system. Accordingly the on-line identification algorithm and interface S/W are used to obtain the on-line FNN model structure and to accomplish the on-line modeling. And using some I/O data gathered partly in the field(plant), computer simulation is carried out to evaluate the performance of FNN model structure generated by the on-line identification algorithm. This simulation results show that the proposed technique can produce the optimal fuzzy model with higher accuracy and feasibility than other works achieved previously.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.526-531
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• 1997

To control nonlinear chemical processes, a new neural linearizing control scheme is proposed. This is a hybrid of a radial basis function(RBF) network and a linear controller, thus the control action applied to the process is the sum of both control actions. Firstly, to train the RBF newtork a linear reference model is determined by analyzing the past operating data of the process. Then, the training of the RBF newtork is iteratively performed to minimize the difference between outputs of the process and the linear reference model. As a result, the apparent dynamics of the process added by the RBF newtork becomes similar to that of the linear reference model. After training, the original nonlinear control problem changes to a linear one, and the closed-loop control performance is improved by using the optimum tuning parameters of the linear controller for the linear dynamics. The proposed control scheme performs control and training simultaneously, and shows a good control performance for nonlinear chemical processes.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2018-2020
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• 1998

In design of a digital current controller for a 3$\phi$ voltage-source (VS) PWM converter, its conventional model, i.e., stationary or synchronous reference frame model, is used in obtaining its discretized version. It introduces, however, inherent errors since the following practical problems are not taken into consideration: the characteristics of the space vector-based pulsewidth modulation (SVPWM) and the time delays in the process of sampling and computation. In this paper, the new hybrid reference frame model of the 3$\phi$ VS PWM converter is proposed considering these problems. In addition, the direct digital current controller based on this model is designed without any prediction or extrapolation algorithm to compensate the time delay. So the control algorithm is made very simple. The validity of the proposed algorithm is proved by the computer simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.12
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• pp.2353-2363
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• 1994

This paper is concerned with the design of a robust digital controller using reduced-order observer on a robotic manipulator under the disturbance. In most cases of robotic manipulator since all state vectors are not measurable, the unmeasurable state vectors must be estimated or reconstructed. Other problems are caused by the nonlinear element like as nondifferentiable Coulomb friction, disturbance due to the gravitational pull, and the torsional spring effect of a link between the drive motor and the manipulator arm. The controller is based on feeding back the observable variables and the estimated state variables which are generated by the observer, and augmenting the system by additional discrete integrators. The feedback gain parameters are obtained by first applying the optimal control theory and then readjusting the feedback parameters to eliminate the limit cycle by using describing Function for nonlinear hybrid system.

• Proceedings of the KIEE Conference
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• summer
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• pp.1251-1253
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neuro-fuzzy control(NFC) and estimation of speed using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.5
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• pp.53-57
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• 2008

Diesel generator is most widely used for supplying of emergency electrical power. There have been extensive research efforts to develop ways to Ensure stable electrical power delivery to the loads using hybrid power sutures, such as power source, storage batteries, fuel cells and solar cells. Furthermore, as the role of these diesel generators for emergency electrical power supply has recently become very important, they should assure high reliability and flexibility according to the operation load. Therefore, in this paper, we introduce a controller to be used in diesel generator toenable tracking control of maximum power according to the load variation and suppressing high-order harmonics while maintaining stable frequency.