• Nuclear Engineering and Technology
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• v.34 no.6
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• pp.553-565
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• 2002

In this paper, the robust control scheme with the improved control performance within the boundary layer is proposed. In the control scheme, the robust controller based on the traditional variable structure control method is modified to have the adaptation within the boundary layer. From this controller, the width of the boundary layer where the robust control input is smoothened out can be given by an appropriate value. But the improved control performance within the boundary layer can be achieved without the so-called control chattering because the role of adaptive control is to compensate for the uncovered portions of the robust control occurred from the continuous approximation within the boundary layer Simulation tests for circular navigation of an underwater wall-ranging robot developed for inspection of wall surfaces in the research reactor, TRIGA MARK III, confirm the performance improvement. Notational Conventions Vectors are written in boldface roman lower-case letters, e.g., x and y. Matrices are written in upper-case roman letters, e.g., G and B. And ∥.∥ means the Euclidean norm.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.221-225
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• 2005

This paper proposes a gain scheduled control technique using time-delay for the nonlinear system with plant uncertainties and unexpected disturbances. The time delay-based gain scheduled control depends on a direct estimation of a function representing the effect of uncertainties. The information from the estimation is used to cancel the unknown dynamics and the unexpected disturbances simultaneously. The proposed estimation scheme with a finite convergence time is formulated in order to estimate the unborn scheduling variable variation. In other words, the time delay-based gain scheduled control uses the past observation of the system's response and the control input to directly modify the control actions rather than to adjust the controller gains or to identify system parameters. It has a simple structure so as to minimize the computational burden. The benefits of this proposed scheme are demonstrated in the simulation of an electromagnetic suspension system with plant uncertainties and external disturbances, and the proposed controller is compared with the conventional state feedback controller.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.202-208
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• 2001

A Switched Reluctance Motor(SRM) has double salient poles structure and the phase windings are wound in stator. SRM hase more simple structure that of other motor, thus manufacture cost is low, mechanically strong, reliable to a poor environment such as high temperature, and maintenance cost is low because of brushless. SRM needs position detector to get rotator position information for phase excitation and tachometer or encoder for constant speed operation. But, this paper doesn\`s use an encoder of high cost for velocity measurement of rotator. Instead of it, the algorithm for position detection and velocity estimation from simple slotted disk has been proposed and developed. To implement variable speed digital control system with velocity estimation algorithm, the TMS320F240-20MIPS fixed point arithmetic processor of TI corporation is used. The experimental results of the developing system are enable to control speed with wide range, not only single pulse, hard chopping mode and soft chopping, ut also variable speed control, and advance angle control.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Journal of IKEEE
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• v.8 no.1 s.14
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• pp.96-107
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• 2004

In this paper, a new integral variable structure regulation controller(IVSRC) is designed by using a special integral sliding surface and a disturbance observer for the improved regulation control of highly nonlinear robot manipulators with prescribed output performance. The sliding surface having the integral state with a special initial condition is employed in this paper to exactly predetermine the ideal sliding trajectory from a given initial condition to origin without any reaching phase. And a continuous sliding mode input using the disturbance observer is also introduced in oder to effectively follow the predetermined sliding trajectory within the prescribed accuracy without large computation burden. The performance of the prescribed tracking accuracy to the predetermined sliding trajectory is clearly investigated in detail through the two theorems together with the closed loop stability. The design of the proposed IVSRC is separated into the performance design and robustness design in each independent link. The usefulness of the algorithm has been demonstrated through simulation studies on the regulation control of a two link manipulator under parameter uncertainties and payload variations, in view of no reaching phase, no overshoot, predetermined response with prescribed accuracy, easy change of output performance, separation of design phase, and so on.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.3
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• pp.60-67
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• 2001

As a method of variable valve train(VVT), Electro-Mechanical Valve(EMV) has been studied. Compared with conventional VVT system, the EMV system has a relatively simple structure. The system has two electromagnets, springs and an armature. The system can be operated by reciprocal action between armature and two electromagnets. And, the operating event can be controlled by electrical signal from controller. Therefore, reduction of emission and fuel consumption can be achieved through valve event control at each engine operating condition. In this study, characteristics of EMV system were investigated by simulations and experiments. The results of simulation and experiment show that the core shape and material characteristics are dominant parameters on magnetic force and delay time. In order to apply the system to commercial engine, it has a compact size and high stiffness springs(50N/mm) to increase the valve speed. Because of high valve seating velocity, loud noise and high impact force generated, which can lead to reduction of actuator durability. Therefore, further research is required to reduce valve seating velocity.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1008-1027
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• 2014

An electric scooter with a V-belt continuously variable transmission (CVT) driven by a permanent magnet synchronous motor (PMSM) has a lot of nonlinear and time-varying characteristics, and accurate dynamic models are difficult to establish for linear controller designs. A PMSM servo-drive electric scooter controlled by a novel hybrid modified recurrent Legendre neural network (NN) control system is proposed to solve difficulties of linear controllers under the occurrence of nonlinear load disturbances and parameters variations. Firstly, the system structure of a V-belt CVT driven electric scooter using a PMSM servo drive is established. Secondly, the novel hybrid modified recurrent Legendre NN control system, which consists of an inspector control, a modified recurrent Legendre NN control with an adaptation law, and a recouped control with an estimation law, is proposed to improve its performance. Moreover, the on-line parameter tuning method of the modified recurrent Legendre NN is derived according to the Lyapunov stability theorem and the gradient descent method. Furthermore, two optimal learning rates for the modified recurrent Legendre NN are derived to speed up the parameter convergence. Finally, comparative studies are carried out to show the effectiveness of the proposed control scheme through experimental results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.612-618
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• 1998

The success of a fuzzy logic control system solving any given problem critically depends on the architecture of th network. Various attempts have been made in optimizing its structure its structure using genetic algorithm automated designs. In a regular genetic algorithm , a difficulty exists which lies in the encoding of the problem by highly fit gene combinations of a fixed-length. This paper presents a new approach to structurally optimized designs of a fuzzy model. We use a messy genetic algorithm, whose main characteristics is the variable length of chromosomes. A messy genetic algorithms used to obtain structurally optimized fuzzy models. Structural optimization is regarded important before neural network based learning is switched into. We have applied the method to the exampled of a cart-pole balancing.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1403-1412
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• 2019

A coupled inductor-dual boost-inverter (CIDBI) with a differential structure has been presented for application to a micro-inverter photovoltaic module system due to its turn ratio of a high-voltage level. However, it is difficult to design a CIDBI converter with a conventional PI regulator to be stable and achieve good dynamic performance, given the fact that it is a high order system. In view of this situation, a sliding mode control (SMC) strategy is introduced in this paper, and two different sliding mode controllers (SMCs) are proposed and adopted in the left and right side of two Boost sub-circuits to implement the corresponding regulation of the voltage and current. The schemes of the SMCs have been elaborated in this paper including the establishment of a system variable structure model, selection of the sliding surface, determination of the control law, and presentation of the reaching conditions and sliding domain. Finally, the mathematic analysis and the proposed SMC are verified by experimental results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1983-1989
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• 2005

Industrial robots are powerful, extremely accurate multi-jointed systems, but they are heavy and highly rigid because of their mechanical structure and motorization. Therefore, sharing the robot working space with its environment is problematic. A novel pneumatic artificial muscle actuator (PAM actuator) has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. Its main advantages are high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks. The PAM is undoubtedly the most promising artificial muscle for the actuation of new types of industrial robots such as Rubber Actuator and PAM manipulators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. In addition, the nonlinearities in the PAM manipulator still limit the controllability. Therefore, it is not easy to realize motion with high accuracy and high speed and with respect to various external inertia loads in order to realize a human-friendly therapy robot To overcome these problems a novel controller, which harmonizes a phase plane switching control method with conventional PID controller and the adaptabilities of neural network, is newly proposed. In order to realize satisfactory control performance a variable damper - Magneto-Rheological Brake (MRB) is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control using neural network brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control using neural network and without regard for the changes of external inertia loads.