Robust DC-DC converter that can function with a single controller over a wide range of load and input voltages is required. In such a case, changes in the output voltage must be suppressed. We propose an aproximate two-degree-of-freedom (2DOF) digital controller that realizes the start-up response and dynamic load response independently. The controller makes the control bandwidth wider and suppresses the variations that occur in the output voltage due to sudden changes in loads and input voltages. In this paper, a new approximate 2DOF digital controller that involves the additinal zeros is proposed. The controller greatly suppresses the variations that occur in the output voltage due to sudden changes in loads and input voltages. This controller is actually implemented on a digital-signal-controller (DSP) and is connected to a DC-DC converter. Experimental studies demonstrate that this digital controller can satisfy the given specifications.
Traffic accidents are big problems in our lives. Most causes of traffic accidents are because of human mistakes. The process of driving consists of three parts: recognition, judgment, and operation. Especially, 70% of the traffic accidents caused by human are recognition mistakes. Therefore, this paper proposes the haptic pedal system to transmit the road condition to the driver. This system assists the driver's braking operation to suppress the wheel slip. In order to convert the brake pedal into haptic pedal, sliding mode controller is applied. Simulation and experiment were conducted to show the validity of the proposed system.
For environment recognition with the camera, it is preferable to reduce the number of images to be processed in order to reduce the processing time. In complicated environments, it is difficult to locate objects and measure their correct positions. We propose an active vision system to solve these issues. An initial position of the camera is known. The camera is installed in a location which an occlusion problem doesn't generate. When the external environment is static, the parallel stereo camera with few amounts of movement is performed from an initial position, and the rough coordinates of each objects are calculated. A model of object trajectories is designed by considering the position and the state of the camera. We adjust the next position of the camera in accordance with this model; thus, we can avoid the problem of occlusion of the objects by calculating the coordinates of the next position of the camera accurately. Finally the accurate coordinates of the objects are calculated by considering the state of the camera and the obtained from the images information. The efficiency of the proposed active vision system is verified by simulations and experiments.
Closed rotor slots are widely employed in low-power squirrel-cage induction motors with die-cast aluminum cage rotors. Die-cast aluminum cages with closed rotor slots can be manufactured commercially. They help reduce flux pulsation in air gaps, attenuate acoustic noises, and achieve high efficiency. However, it is difficult to calculate bridge inductance of a closed rotor slot accurately because the main flux passes through the bridge and iron saturation can be achieved depending upon the bar current. In this study, bridge inductance was investigated by using a search coil and by FEM analysis and conventional equations. The bridge flux density and the bridge linkage flux were measured by using 4P-0.75kW motor with closed rotor slots, and the bridge inductance was calculated as a function of rotor bar current. The bridge inductance was also analyzed by FEM, and the results were analytically checked by using the calculated conventional equations. From these analyses, it is seen that the measured values of the bridge inductance are in good agreement with the values calculated by FEM and conventional methods. It is verified that the bridge inductance shows a trend similar to that of the μ-H curve of the rotor steel sheet.
The purpose of our study is to develop a precise model by applying the technique of system identification for the model-based control of a nonlinear robot arm, under taking joint-elasticity into consideration. We previously proposed a systematic identification method, called “decoupling identification,” for a “SCARA-type” planar two-link robot arm with elastic joints caused by the Harmonic-drive® reduction gears. The proposed method serves as an extension of the conventional rigid-joint-model-based identification. The robot arm is treated as a serial two-link two-inertia system with nonlinearity. The decoupling identification method using link-accelerometer signals enables the serial two-link two-inertia system to be divided into two linear one-link two-inertia systems. The MATLAB®'s commands for state-space model estimation are utilized in the proposed method. Physical parameters such as motor inertias, link inertias, joint-friction coefficients, and joint-spring coefficients are estimated through the identified one-link two-inertia systems using a gray-box approach. This paper describes accuracy evaluations using the two-link arm for the decoupling identification method under introducing closed-loop-controlled elements and varying amplitude-setup of identification-input. Experimental results show that the identification method also works with closed-loop-controlled elements. Therefore, the identification method is applicable to a “PUMA-type” vertical robot arm under gravity.
A control system design method for disturbance suppression in a sampled-data positioning system was studied. To avoid complicated calculations involving matrices, this method uses frequency responses of a controlled object and a digital controller for calculating the gain of the sensitivity function in a sampled-data positioning control system. The method can handle inter-sampling vibrations and the characteristics of disturbance suppression beyond the Nyquist frequency in a sampled-data positioning system. As a result, this study indicates limiting conditions for disturbance suppression in the sampled-data positioning control system. This study also indicates the merits of using a multi-rate control system that includes an interpolator, a multi-rate filter, and a multi-rate hold. In order to verify the validity of the proposed method, simulations and experiments for disturbance suppression in the sampled-data positioning control system were conducted on a head-positioning control system in a hard disk drive.
The objective of this paper is the estimation of unknown static parameters in non-linear non-Gaussian state-space model. The Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is considered due to its highly efficient gradient approximation. We consider a particle filtering method and employ the SPSA algorithm to maximize recursively the likelihood function. Nevertheless, the SPSA algorithm can become inadequate in models as non-Gaussian state-space model. So that, we have proposed to modify the SPSA algorithm in order to estimate parameters very efficiently in complex models as proposed here reducing its computational cost. An efficient parameter estimator as the Finite Difference Stochastic Approximation (FDSA) algorithm is considered here, in order to compare it with the efficiency of the proposed SPSA algorithm. The proposed algorithm can generate maximum likelihood estimates very efficiently. The performance of proposed SPSA algorithm is shown through simulation using a model with highly multimodal likelihood.
The authors devised a novel method to determine the position of correlation peaks resulting from a received spread spectrum signal. This method does not require any threshold or clock adjustment. A simulation and experimental evaluation of this method were performed with an LF-band wireless communication system. The result showed that the system has a clock tolerance of about 1000ppm and is useful for LF communication with limited circuit scale (e.g., an LF wireless tag).
The conventional semiconductor yield analysis is a hypothesis verification process, which heavily depends on engineers' knowledge. Data mining methodology, on the other hand, is a hypothesis discovery process that is free from this constraint. This paper proposes a data mining method for semiconductor yield analysis, which consists of the following two phases: discovering hypothetical failure causes by regression tree analysis and verifying the hypotheses by visualizing the measured data based on engineers' knowledge. It is shown, through experiment under the real environment, that the proposed method detects hypothetical failure causes, which were considered practically impossible to detect, and that yield improvement is achieved by taking preventive actions based on the detected failure causes.
The wide-angle fovea (WAF) sensor comprises a specially made wide-angle fovea lens and a commercially available CCD/CMOS camera with photosensitive elements of uniform size. The sensor realizes a 120-degree-wide field of view (FOV) and high magnification in the central FOV without increasing the number of pixels per image. This paper focuses on the multifunctional use of an input image with space-variant spatial resolution that enables an autonomous mobile robot to avoid obstacles during locomotion. In order to use the WAF-input image efficiently, image processing for central vision, i.e., detection of 3D obstacles, and image processing for peripheral vision, i.e., self-localization of the mobile robot, are performed simultaneously and cooperatively. The comparison of the simulation results of spatial resolutions of the WAF lens and a pinhole camera (PHC) lens shows that the WAF lens can be used for depth measurement in the central FOV and self-localization in the peripheral FOV by the parallel stereo method and the two-parallel-line algorithm, respectively. The results obtained by the WAF lens are more accurate than those obtained by the PHC lens. Autonomous locomotion of the mobile robot has been demonstrated by performing two obstacle avoidance experiments.
This paper presents a rolling friction model-based friction compensation for precise tracking control of linear motor-driven table systems. Rolling friction in mechanisms behaves as a nonlinear elastic element in the micro-displacement region, and deteriorates the tracking performance with slow settling response in positioning. In this paper, therefore, the rolling friction characteristic is mathematically formulated and is adopted to analytical examinations and compensator design to improve the slow settling response. The proposed compensation has been verified by experiments by using a prototype for industrial positioning devices.
Voltage source and current source power converters with single-phase input and three-phase output are presented. Both converters consist of three legs and a three-phase power module only is used. The normal PWM methods with the sinusoidal modulating wave and the triangular carrier wave are employed for sinusoidal waves in ac sides. The simulated waveforms are shown and these results confirm that the converters under the PWM operation can generate the sinusoidal voltages and currents.
In this paper, three-dimensional airgap structure of the motor to improve the torque characteristics without shortening the gap length is proposed. It is shown that the 3-D airgap structure has an effect of shortening a real gap length to about 70%.