A new chattering free PD-sliding mode hybrid control scheme is proposed for robot manipulators. This hybrid controller is composed of a PD controller and a semi-continuous sliding mode controller. It has a good robust performance in reaching mode which does not possess invariance property of sliding mode, and has chattering free characteristics in sliding mode. Thus, the PD-sliding mode hybrid controller has a good robust performance in the whole region. It is shown that the proposed control has a good transient response and trajectory tracking performance for a 2-link SCARA robot manipulator.

This paper deals with a PWM(Pulse Width Modulation) current amplifier using digital controller in order to generate a gradient magnetic field far the MRI(Magnetic Resonance Image) system. Because of tolerance of discrete devices, it is difficult to set accurate values of the control parameters and to make an analog-controlling circuit. However, using digital controller, it is possible to set exact control parameters and to adopt a modern control techniques. It is shown that the digital controller will highly enhance the output current response and it will improve the quality of the MRI.

Controllers for acoustic noise reduction in disk drives have been developed but they have slower seek time performance than time-optimal controllers. We propose a new seek servo controller that has acoustic noise reduction benefit and faster seek time performance than conventional controllers. The proposed controller is designed to make sure that head is moved with maximized acceleration and deceleration under the voltage limitation imposed on head-positioning motor and so it provides faster seek time than conventional controllers designed by considering the current limitation. The experimental results using a commercially available disk drive confirm that the use of the proposed controller results in foster seek time than conventional controllers for acoustic noise reduction.

An FLNN-based neural network controller is applied to precise positioning of XY table with friction as the extension study of [11]. The neural network identifies the frictional farces of the table. Its weight adaptation rule, named the reinforcement adaptive learning rule, is derived from the Lyapunov stability theory. The experimental results with 2-DOF XY table verify the effectiveness of the proposed control scheme. It is also expected that the proposed control approach is applicable to a wide class of mechanical systems.

An optimization approach is used to partition the field of view. A cost function is defined to represent the constraints on the solution, which is then mapped onto a two-dimensional Hopfield neural network for minimization. Each neuron in the network represents a possible match between a field of view and one or multiple objects. Partition is achieved by initializing each neuron that represents a possible match and then allowing the network to settle down into a stable state. The network uses the initial inputs and the compatibility measures between a field of view and one or multiple objects to find a stable state.

The study is concerned with an approach to the design of new architectures of fuzzy neural networks and the discussion of comprehensive design methodology supporting their development. We propose an Adaptive Fuzzy Polynomial Neural Networks(APFNN) based on Fuzzy Neural Networks(FNN) and Self-organizing Networks(SON) for model identification of complex and nonlinear systems. The proposed AFPNN is generated from the mutually combined structure of both FNN and SON. The one and the other are considered as the premise and the consequence part of AFPNN, respectively. As the premise structure of AFPNN, FNN uses both the simplified fuzzy inference and error back-propagation teaming rule. The parameters of FNN are refined(optimized) using genetic algorithms(GAs). As the consequence structure of AFPNN, SON is realized by a polynomial type of mapping(linear, quadratic and modified quadratic) between input and output variables. In this study, we introduce two kinds of AFPNN architectures, namely the basic and the modified one. The basic and the modified architectures depend on the number of input variables and the order of polynomial in each layer of consequence structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the AFPNN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed AFPNN can produce the model with higher accuracy and predictive ability than any other method presented previously.

The electrical characteristics of solid state devices such as BJT(Bipolar Junction Transistor) and MOSFET, etc, are altered by impinging nuclear radiation and temperature in the space environment. This phenomenon is well known and has been studied extensively since the early 1960's when satellites were first being designed and used in the United States. However, the studies and the developments of radiation hardening technologies for the electronic components at the industrial fields in our country has not been popular so far. The worst case design technology in the electrical circuit is required for the appropriate operation of solid state devices in the space environment. In this paper, the interface circuit used in KOMPSAT(Korea Multipurpose Satellite), which is now being operated since the one was launched in 1999, is optimally designed to accomodate the worst case design and radiation effect.

This paper presents a systematic method of the zigzag gait planning for quadruped walking robots. When a robot walks with a zigzag gait, its body is allowed to move from side to side, while the body movement is restricted along a moving direction in conventional continuous gaits. The zigzag movement of the body is effective to improve the gait stability margin. To plan a zigzag gait in a systematic way, the relationship between the center of gravity(COG) and the stability margin is firstly investigated. Then, new geometrical method is introduced to plan a sequence of the body movement which guarantees a maximum stability margin as well as monotonicity along a moving direction. Finally, an optimal swing-leg sequence is chosen for a given arbitrary configuration of the robot. To verify the proposed method, computer simulations have been performed for both cases of a periodic gait and a non-periodic gait.

A 3-dimenstional automatic solder paste inspection system is described that can be used to find defects occurring in solder paste printing process. This system extracts height and volume information very fast as well as area of solder paste printed, using multiple slit ray projection and Galvano-mirror scanning. Methods are presented on calibration of camera and slit projector, real-time image processing of multiple slit images, determination of reference height, and extraction of paste height information are proposed. Performance of the system was successfully demonstrated through field tests.

A mathematical model and dynamic characteristics ova continuously variable damper for semi-active suspen- sion systems are investigated. After analyzing the geometry of a typical continuously variable damper, mathematical models fur individual components including piston, orifices, spring, and valves are first derived and then the flow equations for extension and compression strokes are investigated. To verify the developed mathematical model, the dynamic response of the model are simulated using MATLAB/SIMULINK and are compared with experimental results. The proposed model can be used not only for mechanical components design but also for control system design.

In Strapdown Inertial Navigation System(SDINS), error models based on previously proposed conversion equations between the attitude errors, are only valid in case the attitude errors are small. The SDINS error models have been independently studied according to the definition of the reference frame and of the attitude error. The conversion equations between the attitude errors applicable to SDINS with large attitude errors are newly derived. Lyapunov transformation matrices are also derived from the obtained results. Furthermore the general method, which is independent of the attitude error and the reference frame to derive SDINS error model, is proposed using the Lyapunov transformation.

This paper deals with the transfer alignment problem of SDINS(StrapDown Inertial Navigation System) subjected to roll and pitch motions of the ship. In order to reduce alignment errors induced by ship body flexure, a linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonlinear measurement equation with respect to the dominant y axis component and defining the flexure state of random constant type. And then a robust state estimation scheme is introduced to account for modeling uncertainty of the flexure. By interpreting the simulation results and comparing with the velocity and DCM(Direction Cosine Matrix) partial matching method, it is shown that the proposed method is effective enough to improve the azimuth alignment performance.

A novel GPS initial synchronization scheme with low hardware complexity is proposed. The proposed method has the decomposed differential matched filter, which consists of 25% multiplier and adder of the conventional matched filter. This paper presents the generalized mean acquisition time of initial synchronization scheme with multiple correlator. It is shown that the proposed method, in spite of its low hardware complexity, has the equal performance to the conventional method. The performance of the proposed method is verified through the simulation test by the GPS simulator. It is shown that the proposed method prevents the squaring loss of non-coherent integration.