New Approach for a Fault Detect Model-Based Controller: New Approach for a Fault Detect Model-Based Controller

In this paper, we present a design of a new fault detect model-based (FDMB) controller system. The system is aimed to detect faults quickly and reconfigure the controller accordingly. Thus, such system can perform its function correctly even in the presence of internal faults. An FDMB controller consists of two main parts, the first is fault detection and diagnosis (FDD); and the second is controller reconfiguration (CR). Systems subject to such faults are modelled as stochastic hybrid dynamic model. Each fault is deterministically represented by a mode in a discrete set of models. The FDD is used with interacting multiple-model (IMM) estimator and the CR is used with generalized predictive control (GPC) algorithm. Simulations for the proposed controller are illustrated and analysed

Micro Electromechanical Systems (MEMS) Based Microfluidic Devices for Biomedical Applications

Micro Electromechanical Systems (MEMS) based microfluidic devices have gained popularity in biomedicine field over the last few years. In this paper, a comprehensive overview of microfluidic devices such as micropumps and microneedles has been presented for biomedical applications. The aim of this paper is to present the major features and issues related to micropumps and microneedles, e.g., working principles, actuation methods, fabrication techniques, construction, performance parameters, failure analysis, testing, safety issues, applications, commercialization issues and future prospects. Based on the actuation mechanisms, the micropumps are classified into two main types, i.e., mechanical and non-mechanical micropumps. Microneedles can be categorized according to their structure, fabrication process, material, overall shape, tip shape, size, array density and application. The presented literature review on micropumps and microneedles will provide comprehensive information for researchers working on design and development of microfluidic devices for biomedical applications

Piezoelectric Energy Generation and Harvesting at the Nano-Scale: Materials and Devices

Continuous efforts are being made for alternative power generation techniques for use in devices with sub-micron-scale dimensions. In this work, we have perused through some of these efforts, focusing mainly on devices using materials with piezoelectric properties. In the last decade or so, nanostructured zinc oxide (ZnO) has drawn worldwide attention for its path-breaking properties. One of its most extensively-studied properties is its ability to generate power when subjected to mechanical vibration. It can generate a potential within a wide range of frequency vibrations, from a few Hz to thousands of KHz. This can lead to extensive application prospects in many important fields, like self-power generating devices for medical applications, wireless technologies and various sensors, etc. This review looks into reports related to such technology in detail. It also takes into account certain other materials that have been reported for piezoelectric energy scavenging applications

Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot

This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles

A production throughput forecasting system in an automated hard disk drive test operation using GRNN

Purpose: The goal of this paper is to develop a pragmatic system of a production throughput forecasting system for an automated test operation in a hard drive manufacturing plant. The accurate forecasting result is necessary for the management team to response to any changes in the production processes and the resources allocations. Design/methodology/approach: In this study, we design a production throughput forecasting system in an automated test operation in hard drive manufacturing plant. In the proposed system, consists of three main stages. In the first stage, a mutual information method was adopted for selecting the relevant inputs into the forecasting model. In the second stage, a generalized regression neural network (GRNN) was implemented in the forecasting model development phase. Finally, forecasting accuracy was improved by searching the optimal smoothing parameter which selected from comparisons result among three optimization algorithms: particle swarm optimization (PSO), unrestricted search optimization (USO) and interval halving optimization (IHO). Findings: The experimental result shows that (1) the developed production throughput forecasting system using GRNN is able to provide forecasted results close to actual values, and to projected the future trends of production throughput in an automated hard disk drive test operation; (2) An IHO algorithm performed as superiority appropriate optimization method than the other two algorithms. (3) Compared with current forecasting system in manufacturing, the results show that the proposed system’s performance is superior to the current system in prediction accuracy and suitable for real-world application. Originality/value: The production throughput volume is a key performance index of hard disk drive manufacturing systems that need to be forecast. Because of the production throughput forecasting result is useful information for management team to respond to any changing in production processes and resources allocation. However, a practically forecasting system for production throughput has not been described in detail yet. The experiments were conducted on a real data set from the final testing operation of hard disk drive manufacturing factory by using Visual Basics Application on Microsoft Excel© to develop preliminary forecasting system on testing and verification process. The experimental result shows that the proposed model is superior to the performance of the current forecasting system

Mobile Robot Integrated with Gyroscope by Using IKF

This paper mainly proposes absolute positioning instruments using camera positioning system and compass. The absolute positioning systems are used to estimate absolute position and orientation errors combined with estimated position and orientation from differential odometry integrated with gyroscope to calculate absolute position and orientation of mobile robot. In the method, the indirect Kalman filter is used to estimate absolute position and orientation errors and the estimated errors are fed back to odometry system, and also estimates some parameter errors to correct odometry system and gyroscope error. The simulation and experimental results show the estimated position and orientation of odometry system integrated with gyroscope, systematic errors of odometry system and gyroscope, absolute position from the camera positioning system and absolute orientation from compass compared with odometry system integrated with gyroscope

Modeling, simulation and control of high speed nonlinear hydraulic servo system

Abstract. The goal of this paper is to present for modeling a Hydraulic Servo System (HSS). This work describes the design and implementation of a control system for the operation of a hydraulic mini press machine. First, we develop mathematical models for obtaining the system responses. These responses of the servo valve, and open loop HSS are given step and sinusoidal inputs. While, the closed loop system is based on linearized model of feedback regulator of PD controller for high-speed control. All models and controllers are simulated using MATLAB and SIMULINK computer program. An experimental set-up is constructed, which consists of micro-controller PIC 18F458 as controller, a servo valve driven HSS, and feedback elements. The result shows that, HSS can provide higher speed of response with fast motion of the plant and its performance is compared with three alternative high speed nonlinear HSS. It is shown that, proposed method is superior to existing ones