DC-DCゼータコンバータのロバスト安定化のためのスイッチング制御方策

京都大学新制・課程博士博士(情報学)甲第23545号情博第775号新制||情||132(附属図書館)京都大学大学院情報学研究科数理工学専攻(主査)教授 太田 快人, 教授 山下 信雄, 教授 大塚 敏之学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

An Implementation Of Full-State Observer And Controller For Dynamic State-Space Model Of Zeta Converter

Zeta converter is a fourth order dc-dc converter that can increases (step-up) or decreases (step-down) the input voltage. The converter needs feedback control to regulate its output voltage. A full-state observer can be used to estimate the states of the system in condition the output must be observable. The estimated states can be fed to full-state feedback controller to control the plant. This paper presents the dynamic model of zeta converter. The converter is modeled using state-space averaging (SSA) technique. Full-state observer and controller are implemented on the converter to regulate the output voltage. The simulation results are presented to verify the accuracy of the modeling and the steady-state performance subjected to input and load disturbances

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique

OBSERVER-BASED-CONTROLLER FOR INVERTED PENDULUM MODEL

This paper presents a state space control technique for inverted pendulum system. The system is a common classical control problem that has been widely used to test multiple control algorithms because of its nonlinear and unstable behavior. Full state feedback based on pole placement and optimal control is applied to the inverted pendulum system to achieve desired design specification which are 4 seconds settling time and 5% overshoot. The simulation and optimization of the full state feedback controller based on pole placement and optimal control techniques as well as the performance comparison between these techniques is described comprehensively. The comparison is made to choose the most suitable technique for the system that have the best trade-off between settling time and overshoot. Besides that, the observer design is analyzed to see the effect of pole location and noise present in the system

A Review of Resonant Converter Control Techniques and The Performances

paper first discusses each control technique and then gives experimental results and/or performance to highlights their merits. The resonant converter used as a case study is not specified to just single topology instead it used few topologies such as series-parallel resonant converter (SPRC), LCC resonant converter and parallel resonant converter (PRC). On the other hand, the control techniques presented in this paper are self-sustained phase shift modulation (SSPSM) control, self-oscillating power factor control, magnetic control and the H-∞ robust control technique

Real-Time Optimal Control Technique of A Rotary Inverted Pendulum System

This paper presents a real time control technique to stabilize inverted pendulum in the vertical upright position. Stabilize the inverted pendulum is a classical control problem that could be related to some problems in industrial applications. Two common problems that always been encountered by inverted pendulum system is unstable behavior and nonlinear. This lead to numerous studies on the control algorithm to balance the inverted pendulum system in the vertical upright position. Generally, inverted pendulum is mounted on DC motor and is equipped with sensor to measure angular displacement. Inverted pendulum has the same analogy with human that try to balance a broomstick using fingertip. Balancing the Inverted Pendulum requires a good control system. Therefore an optimal control technique is proposed to achieve desired design requirement which are less than 5% overshoot and less than 5 seconds settling time. The controller is optimized to achieve the best performance result. Finally the performance of the controller is compared with PID controller as a benchmark

Low-cost and portable automatic sheet cutter

Process automation is crucial to increase productivity, more efficient use of materials, better product quality, improved safety, etc. In small-medium enterprise (SME) businesses related to household retailing, one of the process automation needed is the measurement and cutting of the mat or sheet, made of rubber or polyvinyl chloride (PVC) materials. Most of the household retailers that selling the sheet, the process of measuring and cutting according to the customer’s requirements are manually performed using a measuring tape and scissors. These manual processes can cause inaccuracy in length, inefficient use of material, low productivity and reduce product quality. This paper presents a low cost and portable automatic sheet cutter using the Arduino development board, which is used to control the process of measuring and cutting the materials. The system uses a push-button where the user can set the required length and quantity of the sheet. Once the required information is set, the stepper motor rolls the sheet until the required length is satisfied. Subsequently, another stepper motor moves the cutter horizontally and cut the sheet. With the automatic sheet cutter, the material is cut with acceptable precision. The design of the automatic sheet cutter is low cost and portable which significantly suitable to be used by SME household retailers

Design and Implementation of Multiplexed and Obfuscated Physical Unclonable Function

Model building attack on Physical Unclonable Functions (PUFs) by using machine learning (ML) techniques has been a focus in the PUF research area. PUF is a hardware security primitive which can extract unique hardware characteristics (i.e., device-specific) by exploiting the intrinsic manufacturing process variations during integrated circuit (IC) fabrication. The nature of the manufacturing process variations which is random and complex makes a PUF realistically and physically impossible to clone atom-by-atom. Nevertheless, its function is vulnerable to model-building attacks by using ML techniques. Arbiter-PUF is one of the earliest proposed delay-based PUFs which is vulnerable to ML-attack. In the past, several techniques have been proposed to increase its resiliency, but often has to sacrifice the reproducibility of the Arbiter-PUF response. In this paper, we propose a new derivative of Arbiter-PUF which is called Mixed Arbiter-PUF (MA-PUF). Four Arbiter-PUFs are combined and their outputs are multiplexed to generate the final response. We show that MA-PUF has good properties of uniqueness, reliability, and uniformity. Moreover, the resilient of MA-PUF against ML-attack is 15% better than a conventional Arbiter-PUF. The predictability of MA-PUF close to 65% could be achieved when combining with challenge permutation technique

Predicting EMG Based Elbow Joint Torque Model Using Multiple Input ANN Neurons for Arm Rehabilitation

This paper illustrates the Artificial Neural Network (ANN) technique to estimate the joint torque estimation model for arm rehabilitation device in a clear manner. This device acts as an exoskeleton for people who had failure of their limb. Arm rehabilitation device may help the rehab program to whom suffered with arm disability. The device used to facilitate the tasks of the program should improve the electrical activity in the motor unit and minimize the mental effort of the user. Electromyography (EMG) is the techniques to analyze the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person is failed to contract the muscle for movements. To prevent the muscles from paralysis becomes spasticity the force of movements should minimize the mental efforts. Besides that, in order to minimize the used of mental forced for disable patients, the rehabilitation device can be utilize by analyzing the surface EMG signal of normal people that can be implemented to the device. The objective of this work is to model the muscle EMG signal to torque for a motor control of the arm rehabilitation device using ANN technique. The EMG signal is collected from Biceps Brachii muscles to estimate the elbow joint torque. A two layer feed-forward network is trained using Back Propagation Neural Network (BPNN) to model the EMG signal to torque value. The experimental results show that ANN can well represent EMG-torque relationship for arm rehabilitation device control

Solar PV Project Implementation Feasibility Study based on Feed-in Tariff in Malaysia

This paper illustrates the solar PV project implementation feasibility study based on Feed-in tariff embark by Malaysian government. The objectives of this study are to increase the awareness about the benefit of Feed-in Tariff (FiT) and to design a framework for solar PV project implementation in Malaysia. FIT is established to offer a guaranteed pricing structure for renewable energy production such as wind, solar, biogas and biogas. This could encourage greater investments in a renewable energy field in Malaysia. The framework is started by explaining the project lifecycle to set the milestone follow by explain the project Work Breakdown Structure (WBS) and Organization Breakdown Structure (OBS). Finally a proper project scheduling is established ensure a success project implementation