Design of EDFA Gain Controller based on Disturbance Observer Technique

Based on a theoretical erbium-doped fiber amplifier (EDFA) model, we have proposed an application of disturbance observer(DOB) with proportional/integral/differential(PID) controller to EDFA for minimizing gain-transient time of wavelength -division-multiplexing (WDM) multi channels in optical amplifier in channel add/drop networks. We have dramatically reduced the gain-transient time to less than 30μsec by applying DOB with PID controller to the control of amplifier gain. The proposed DOB-based gain control algorithm for EDFA was implemented as a digital control system using TI's DSP(TMS320C28346) chip and experimental results of the system verify the excellent performance of the proposed gain control methodology.

An Investigative Study into Observer based Non-Invasive Fault Detection and Diagnosis in Induction Motors

A new observer based fault detection and diagnosis scheme for predicting induction motors- faults is proposed in this paper. Prediction of incipient faults, using different variants of Kalman filter and their relative performance are evaluated. Only soft faults are considered for this work. The data generation, filter convergence issues, hypothesis testing and residue estimates are addressed. Simulink model is used for data generation and various types of faults are considered. A comparative assessment of the estimates of different observers associated with these faults is included.

Improved Torque Control of Electrical Load Simulator with Parameters and State Estimation

ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.

Design of Nonlinear Observer by Using Chebyshev Interpolation based on Formal Linearization

This paper discusses a design of nonlinear observer by a formal linearization method using an application of Chebyshev Interpolation in order to facilitate processes for synthesizing a nonlinear observer and to improve the precision of linearization. A dynamic nonlinear system is linearized with respect to a linearization function, and a measurement equation is transformed into an augmented linear one by the formal linearization method which is based on Chebyshev interpolation. To the linearized system, a linear estimation theory is applied and a nonlinear observer is derived. To show effectiveness of the observer design, numerical experiments are illustrated and they indicate that the design shows remarkable performances for nonlinear systems.

Design of a Non-linear Observer for VSI Fed Synchronous Motor

This paper discusses two observers, which are used for the estimation of parameters of PMSM. Former one, reduced order observer, which is used to estimate the inaccessible parameters of PMSM. Later one, full order observer, which is used to estimate all the parameters of PMSM even though some of the parameters are directly available for measurement, so as to meet with the insensitivity to the parameter variation. However, the state space model contains some nonlinear terms i.e. the product of different state variables. The asymptotic state observer, which approximately reconstructs the state vector for linear systems without uncertainties, was presented by Luenberger. In this work, a modified form of such an observer is used by including a non-linear term involving the speed. So, both the observers are designed in the framework of nonlinear control; their stability and rate of convergence is discussed.

Stable Robust Adaptive Controller and Observer Design for a Class of SISO Nonlinear Systems with Unknown Dead Zone

This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.

Neural Network Based Predictive DTC Algorithm for Induction Motors

In this paper, a Neural Network based predictive DTC algorithm is proposed .This approach is used as an alternative to classical approaches .An appropriate riate Feed - forward network is chosen and based on its value of derivative electromagnetic torque ; optimal stator voltage vector is determined to be applied to the induction motor (by inverter). Moreover, an appropriate torque and flux observer is proposed.

Modeling and Simulation of Position Estimation of Switched Reluctance Motor with Artificial Neural Networks

In the present study, position estimation of switched reluctance motor (SRM) has been achieved on the basis of the artificial neural networks (ANNs). The ANNs can estimate the rotor position without using an extra rotor position sensor by measuring the phase flux linkages and phase currents. Flux linkage-phase current-rotor position data set and supervised backpropagation learning algorithm are used in training of the ANN based position estimator. A 4-phase SRM have been used to verify the accuracy and feasibility of the proposed position estimator. Simulation results show that the proposed position estimator gives precise and accurate position estimations for both under the low and high level reference speeds of the SRM

Study on the Relations between One's Personality Dimensions and his Personality Judgment about Friend based on Reality Distortion

Judgment is affected by many agents and distortion in this assessment is unpreventable. Personality dimensions are among those factors that interfere with the distortion. In this research, the relations between personality dimensions of subject and his judgment on friends- personality dimensions is investigated. One-hundred friend couples completed both NEO Five Factor Inventory (NEOFFI) and Ahvaz Reality Distortion Inventory (ARDI) to make judgments about themselves and their friends. Observations show that judge-s Agreement and Neuroticism dimensions are impressed by reality distortion. On the other hand, this reality distortion interferes with one-s evaluation of his friend-s Agreement, Neuroticism, and Conscientiousness dimensions. Conscientiousness with suppressive effect on judge-s other dimensions plays the irrelevant role on personality judgment. Therefore, observer-rating tools which are used as a conventional criterion seem to be not valid because of the reality distortion due to judge-s personality dimensions.

Backstepping Sliding Mode Controller Coupled to Adaptive Sliding Mode Observer for Interconnected Fractional Nonlinear System

Performance control law is studied for an interconnected fractional nonlinear system. Applying a backstepping algorithm, a backstepping sliding mode controller (BSMC) is developed for fractional nonlinear system. To improve control law performance, BSMC is coupled to an adaptive sliding mode observer have a filtered error as a sliding surface. The both architecture performance is studied throughout the inverted pendulum mounted on a cart. Simulation result show that the BSMC coupled to an adaptive sliding mode observer have stable control law and eligible control amplitude than the BSMC.

The Advent of Electronic Logbook Technology - Reducing Cost and Risk to Both Marine Resources and the Fishing Industry

Fisheries management all around the world is hampered by the lack, or poor quality, of critical data on fish resources and fishing operations. The main reasons for the chronic inability to collect good quality data during fishing operations is the culture of secrecy common among fishers and the lack of modern data gathering technology onboard most fishing vessels. In response, OLRAC-SPS, a South African company, developed fisheries datalogging software (eLog in short) and named it Olrac. The Olrac eLog solution is capable of collecting, analysing, plotting, mapping, reporting, tracing and transmitting all data related to fishing operations. Olrac can be used by skippers, fleet/company managers, offshore mariculture farmers, scientists, observers, compliance inspectors and fisheries management authorities. The authors believe that using eLog onboard fishing vessels has the potential to revolutionise the entire process of data collection and reporting during fishing operations and, if properly deployed and utilised, could transform the entire commercial fleet to a provider of good quality data and forever change the way fish resources are managed. In addition it will make it possible to trace catches back to the actual individual fishing operation, to improve fishing efficiency and to dramatically improve control of fishing operations and enforcement of fishing regulations.

Nonlinear Observer Design and Sliding Mode Control of Four Rotors Helicopter

In this paper; we are interested in dynamic modelling of quadrotor while taking into account the high-order nonholonomic constraints as well as the various physical phenomena, which can influence the dynamics of a flying structure. These permit us to introduce a new state-space representation and new control scheme. We present after the development and the synthesis of a stabilizing control laws design based on sliding mode in order to perform best tracking results. It ensures locally asymptotic stability and desired tracking trajectories. Nonlinear observer is then synthesized in order to estimate the unmeasured states and the effects of the external disturbances such as wind and noise. Finally simulation results are also provided in order to illustrate the performances of the proposed controllers.

Sexual behaviour and Semen Characteristics of Young Male Boer Goats in Tropical Condition: A Case in Indonesia

Sexual behavior and semen charactertistics were evaluated in young male Boer goats in tropical condition during time period of September to November 2009. The animal was let to have adaptation for five months after importation from Australian climate. A total of 20 bucks were observed for sexual behavior and ability of semen production. Out of this number, 4 faild to libido and 3 produced poor semen. The remaing 13 animals were divided into three groups according to the ages (11-13, 15-16 and 18-25 months). Sexual behavior consisting response time to female teaser, ejaculation time, fixing strenght to female and erection status were normaly observer in 13 bucks, and there was no significant difference between age groups. Semen characteristics from 13 bucks were in normal quality in the volume, sperm mass motility, individual motility, percentage of live- and abnormal sperm. We concluded that is possible to collect semen of Boer goats during the period of September to November under tropical condition. Collection during other time period should be analyzed.

Observer Design for Ecological Monitoring

Monitoring of ecological systems is one of the major issues in ecosystem research. The concepts and methodology of mathematical systems theory provide useful tools to face this problem. In many cases, state monitoring of a complex ecological system consists in observation (measurement) of certain state variables, and the whole state process has to be determined from the observed data. The solution proposed in the paper is the design of an observer system, which makes it possible to approximately recover the state process from its partial observation. The method is illustrated with a trophic chain of resource – producer – primary consumer type and a numerical example is also presented.

Design of Nonlinear Observer by Using Augmented Linear System based on Formal Linearization of Polynomial Type

The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.

A Novel Nucleus-Based Classifier for Discrimination of Osteoclasts and Mesenchymal Precursor Cells in Mouse Bone Marrow Cultures

Bone remodeling occurs by the balanced action of bone resorbing osteoclasts (OC) and bone-building osteoblasts. Increased bone resorption by excessive OC activity contributes to malignant and non-malignant diseases including osteoporosis. To study OC differentiation and function, OC formed in in vitro cultures are currently counted manually, a tedious procedure which is prone to inter-observer differences. Aiming for an automated OC-quantification system, classification of OC and precursor cells was done on fluorescence microscope images based on the distinct appearance of fluorescent nuclei. Following ellipse fitting to nuclei, a combination of eight features enabled clustering of OC and precursor cell nuclei. After evaluating different machine-learning techniques, LOGREG achieved 74% correctly classified OC and precursor cell nuclei, outperforming human experts (best expert: 55%). In combination with the automated detection of total cell areas, this system allows to measure various cell parameters and most importantly to quantify proteins involved in osteoclastogenesis.