شبیه سازی آماده برق کنترل با متلب

شبیه سازی آماده و انجام شده برق کنترل
گروه ترجمه روز، شبیه سازی های آماده و انجام شده دقیق و کامل مقاله های مهندسی برق گرایش کنترل، توسط نرم افزار قدرتمند متلب را با قیمتی ارزان در اختیار دوستان قرار می دهد.  برای شبیه سازی های آماده بیشتر یا شبیه سازی مقالات و پروژه هایتان از صفر، از طرق زیر اقدام نمایید.
وجه: قبل از خرید، خروجی و گزارش کار برای اطمینان شما فرستاده خواهد شد.

 

توجه: این شبیه سازی های اماده، فقط در انحصار وب سایت ترجمه روز می باشد و در هیچ سایتی دیگری پیدا نمی شوند.

تماس، تلگرام، واتس آپ، سروش و ایمیل جهت سفارش و ارسال فایل ها به صورت زیر است:

09027952876

tarjomehrooz@gmail.com

ای دی و یوزر نیم تلگرام جهت جهت سفارش و ارسال فایل ها:

http://www.telegram.me/tarjomehrooz

ای دی و یوزر نیم سروش جهت سفارش و ارسال فایل ها:

http://www.sapp.ir/trooz





کد c1:

سال انتشار 2006  

عنوان مقاله:

Fault Isolation Filter with Linear Matrix Inequality Solution to Optimal Decoupling

چکیده مقاله:

Abstract—In this paper we consider a model–based fault detection and isolation problem for linear time–invariant dynamic systems subject to faults and disturbances. We use an observer scheme that cancels the system dynamics and defines a residual vector signal that is sensitive only to faults and disturbances.We then design a stable fault isolation filter such that the H∞–norm of the transfer matrix function from disturbances to the residual is minimized (for fault detection) subject to the constraint that the transfer matrix function from faults to residual is equal to a pre–assigned diagonal transfer matrix (for fault isolation). The optimization of disturbance decoupling is accomplished via the help of linear matrix inequalities. A numerical example is also presented to illustrate the algorithm

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کد c2:

سال انتشار 2009  

عنوان مقاله:

Nonlinear Control of a Quadrotor Micro-UAV using Feedback-Linearization

چکیده مقاله:

Abstract-Four-rotor micro aerial robots, so called quadrotor DAVs, are one of the most preferred type of unmanned aerial vehicles for near-area surveillance and exploration both in military and commercial in- and outdoor applications. The reason is the very easy construction and steering principle using four rotors in a cross configuration. However, stabilizing control and guidance of these vehicles is a difficult task because of the nonlinear dynamic behavior. In addition, the small payload and the reduced processing power of the onboard electronics are further limitations for any control system implementation. This paper describes the development of a nonlinear vehicle control system based on a decomposition into a nested structure and feedback linearization which can be implemented on an embedded microcontroller. Some first simulation results underline the performance of this new control approach for the current realization

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کد c3:

سال انتشار 2009  

عنوان مقاله:

Adaptive Unscented Kalman Filter with Multiple Fading Factors for Pico Satellite Attitude Estimation

چکیده مقاله:

Abstract—Thus far, Kalman filter based attitude estimation algorithms have been used in many space applications. When the issue of pico satellite attitude estimation is taken into consideration, general linear approach to Kalman filter becomes insufficient and Extended Kalman Filters (EKF) are the types of filters, which are designed in order to overrun this problem. However, in case of attitude estimation of a pico satellite via magnetometer data, where the nonlinearity degree of both dynamics and measurement models are high, EKF may give inaccurate results. Unscented Kalman Filter (UKF) that does not require linearization phase and so Jacobians can be preferred instead of EKF in such circumstances. Nonetheless, if the UKF is built with an adaptive manner, such that, faulty measurements do not affect attitude estimation process, accurate estimation results even in case of measurement malfunctions can be guaranteed. In this study an Adaptive Unscented Kalman Filter with multiple fading factors based gain correction is introduced and tested on the attitude estimation system of a pico satellite by
the use of simulations

Keywords-multiple fading factors; adaptive Kalman filter; Uncented Kalman Filter; attitude estimation

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کد c4:

سال انتشار 2012  

عنوان مقاله:

KF-based Adaptive UKF Algorithm and its Application for Rotorcraft UAV Actuator Failure Estimation

چکیده مقاله:

Abstract: A new adaptive Unscented Kalman Filter (UKF) algorithm for actuator failure estimation is proposed. A
novel filter method with the ability to adapt to the statistical characteristics of noise is presented to improve the estimation accuracy of traditional UKFs. A new algorithm (Kalman Filter (KF) ‐based adaptive UKF), with the ability to adapt to the statistical characteristic of noise, is proposed to improve the UKF’s performance. Such an adaptive mechanism is intended to compensate for the lack of prior knowledge. The asymptotic property of the adaptive UKF is discussed. Actuator Healthy Coefficients (AHCs) are introduced to denote the actuator failure model while the adaptive UKF is employed for the online estimation of both the flight states and the AHCs’ parameters of a rotorcraft UAV (RUAV). Simulations are conducted using the model of a ServoHeli‐90 RUAV from the Shenyang Institute of Automation, CAS. The results are compared with those obtained by normal UKF to demonstrate the effectiveness and improvements of the adaptive UKF algorithm. Besides this, we also compare this algorithm with the MIT‐based one which we proposed in previous research
Keywords: UKF, AHCs, RUAV

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کد c5:

سال انتشار 2014  

عنوان مقاله:

Robust extended Kalman filter for attitude estimation with multiplicative noises and unknown external disturbances

چکیده مقاله:

Abstract: This study is concerned with the robust extended Kalman filtering problem for non-linear attitude estimation systems with multiplicative noises and unknown external disturbances. The multiplicative noises are modelled by random variables with bounded variance. The unknown external disturbances are described to lie in bounded set. The objective of the addressed attitude estimation problem is to design a filter such that, in the presence of both the multiplicative noises and unknown external disturbances, an optimised upper bound on the state estimation error variance can be guaranteed. Thus, a robust extended Kalman filter (REKF) is presented for attitude estimation with multiplicative noises and unknown external disturbances. Compared with the traditional extended Kalman filter in attitude estimation, the proposed algorithm takes into consideration the effects of multiplicative noises and unknown external disturbances. Moreover, the stability of the proposed REKF can be proved under certain conditions by utilising the stochastic stability theory. Finally, the simulation results demonstrate the effectiveness of the proposed REKF

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کد c6:

سال انتشار 2015  

عنوان مقاله:

Optimal Kalman Filter for state estimation of a quadrotor UAV

چکیده مقاله:

Abstract: In this work, the main objective is to study the Optimal Kalman Filtering (OKF) method for estimating the state vector of a small quadrotor UAV through incorporating the internal disturbances including the white Gaussian process and measurement noises. Firstly, the kinematic and dynamic model of the quadrotor is transformed into a discrete-time system via the linear extrapolation method. Secondly, for the sake of performing the high accuracy position and attitude tracking control of the quadrotor, the discrete-time flight controller is designed using second order discrete-time sliding mode technique. In addition, the estimation of the quadrotor aircraft’s state vector is carried out with the use of OKF. The performance of the combination between the flight controller and the OKF is evaluated through simulation tests. Extensive simulation results show that the combined strategy has a good performance in terms of variance and state estimation

Keywords: quadrotor UAV; state estimation; Optimal Kalman Filter; second order discrete-time sliding mode technique

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کد c7:

سال انتشار 2015  

عنوان مقاله:

Kalman Filter based Target Tracking for Track While Scan Data Processing

چکیده مقاله:

Abstract— The targets parameter to be measured for tracking are its relative position in range, azimuth angle, elevation angle and velocity. These parameters can be measured by tracking radar systems. Upon keeping the tracking of these measured parameters the tracker predict their future values. Fire control and missile guidance can be assisted through target tracking only. In fact missile guidance cannot be achieved without tracking the target properly. To predict target parameters (future samples) between scans, track while scan radar system sample each target once per scan interval by using sophisticated smoothing and prediction filters among which alpha-beta-gamma (???) and Kalman filters are commonly used. The principle of recursive tracking and prediction filters are proposed in this paper for two maneuvering targets (lazy and aggressive maneuvering), by implementing the second and third order one dimensional fixed gain polynomial filter trackers. Finally the equations for an n-dimensional multi state kalman filter are implemented and analyzed. In order to evaluate the performance of tracking filters the target considered in this paper is a Novator K100 Indian/Russian air-to-air missile designed to fly at Mach 4. In this paper the main objective of developing these filter tracking algorithmsis to reduce the measurement noise and tracking filter must be capable of tracking maneuvering targets with small residualtracking errors
Keywords— alpha-beta-gamma (???), Kalman filters and Residual error

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کد c8:

سال انتشار 1999  

عنوان مقاله:

FREQUENCY ESTIMATION OF DISTORTED POWER SYSTEM SIGNALS USING EXTENDED COMPLEX KALMAN FILTER

چکیده مقاله:

Abstract – The paper proposes an extended complex Kalman filter and employs it for the estimation of power
system frequency in the presence of random noise and distortions. From the discrete values of the 3-phase voltage
signals of a power system, a complex voltage vector is formed using the well known @-transform. A nonlinear
state space formulation is then obtained for this complex signal and an extended Kalman filtering approach is used to compute the true state of the model iteratively with significant noise and harmonic distortions. As the frequency
is modeled as a state, the estimation of the state vector yields the unknown power system frequency. Several computer simulations test results are presented in the paper to highlight the usefulness of this approach in estimating near nominal and off-nominal power system frequencies
Keywords– Power system frequency, Frequency estimation, Extended Kalman filter, Nonlinear filter

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کد c9:

سال انتشار 2009  

عنوان مقاله:

Adaptive Unscented Kalman Filter with Multiple Fading Factors for Pico Satellite Attitude Estimation

چکیده مقاله:

Abstract—Thus far, Kalman filter based attitude estimation algorithms have been used in many space applications. When the issue of pico satellite attitude estimation is taken into consideration, general linear approach to Kalman filter becomes insufficient and Extended Kalman Filters (EKF) are the types of filters, which are designed in order to overrun this problem. However, in case of attitude estimation of a pico satellite via magnetometer data, where the nonlinearity degree of both dynamics and measurement models are high, EKF may give inaccurate results. Unscented Kalman Filter (UKF) that does not require linearization phase and so Jacobians can be preferred instead of EKF in such circumstances. Nonetheless, if the UKF is built with an adaptive manner, such that, faulty measurements do not affect attitude estimation process, accurate estimation results even in case of measurement malfunctions can be guaranteed. In this study an Adaptive Unscented Kalman Filter with multiple fading factors based gain correction is introduced and tested on the attitude estimation system of a pico satellite by
the use of simulations
Keywords-multiple fading factors; adaptive Kalman filter; Uncented Kalman Filter; attitude estimation

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کد c10:

سال انتشار 2008  

عنوان مقاله:

A two-stage ensemble Kalman filter for smooth data assimilation

چکیده مقاله:

Abstract: The ensemble Kalman Filter (EnKF) applied to a simple fire propagation model by a nonlinear convection-diffusion-reaction partial differential equation breaks down because the EnKF creates nonphysical ensemble members with large gradients. A modification of the EnKF is proposed by adding a regularization term that penalizes large gradients. The method is implemented by applying the EnKF formulas twice, with the regularization term as another observation. The regularization step is also interpreted as a shrinkage of the prior distribution. Numerical results are given to illustrate success of the new method

Keywords : Data assimilation · Ensemble Kalman filter · State-space model · Penalty · Tikhonov regularization · Wildfire · Convection-reaction-diffusion · Shrinkage · Bayesian

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کد c11:

سال انتشار 2011  

عنوان مقاله:

Dynamic State Estimation in Power System by Applying the Extended Kalman Filter With Unknown Inputs to Phasor Measurements

چکیده مقاله:

Abstract—Availability of the synchronous machine angle and speed variables give us an accurate picture of the overall condition of power networks leading therefore to an improved situational awareness by system operators. In addition, they would be essential in developing local and global control schemes aimedat enhancing system stability and reliability. In this paper, the extended Kalman filter (EKF) technique for dynamic state estimation of a synchronous machine using phasor measurement unit (PMU) quantities is developed. The simulation results of the EKF approach show the accuracy of the resulting state estimates. However, the traditional EKF method requires that all externally observed variables, including input signals, be measured or available, which may not always be the case. In synchronous machines, for example, the exciter output voltage may not be available for measuring in all cases. As a result, the extended Kalman filter with unknown inputs, referred to as EKF-UI, is proposed for identifying and estimating the states and the unknown inputs of the synchronous machine simultaneously. Simulation results demonstrate the efficiency and accuracy of the EKF-UI method under noisy or fault conditions, compared to the classic EKF approach and confirms its great potential in cases where there is no access to the input signals of the system

Index Terms—Dynamic state estimation, extended Kalman filtering, phasor measurements, power grid monitoring, power system operation, state estimation, synchronous generator

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کد c12:

سال انتشار 2012  

عنوان مقاله:

Bayesian state estimation of a flexible industrial robot

چکیده مقاله:

A sensor fusion method for state estimation of a flexible industrial robot is developed. By measuring the acceleration at the end-effector, the accuracy of the arm angular position, as well as the estimated position of the end-effector are improved. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; the extended Kalman filter and the particle filter. In a simulation study on a realistic flexible industrial robot, the angular position performance is shown to be close to the fundamental Cramér-Rao lower bound. The technique is also verified in experiments on an ABB robot, where the dynamic performance of the position for the end-effector is significantly improved

Keywords: Industrial robot , Positioning , Estimation , Particle filter , Extended Kalman filter , Cramér–Rao lower bound

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کد c13:

سال انتشار 2014

عنوان مقاله:

Aircraft Control System Using LQG and LQR Controller with Optimal Estimation-Kalman Filter Design

سیستم کنترل هواپیما با استفاده از کنترل کننده LQR و LQG با طراحی تخمینگر فیلتر کالمن بهینه

چکیده مقاله:

این مقاله یک کنترل کننده مقاوم LQR و LQG برای دینامیک های یک سیستم هواپیما توصیف می کند. کنترل کننده برای دستیابی شرایط پایداری مقاوم و عملکرد دینامیکی خوب در برابر تغییرات پارامترهای هواپیما می­باشد. کاربرد طرح کنترلی LQR و LQG پیشنهادی در میان شبیه سازی ها اجرا شده است. کنترل کننده مقاوم پیشنهادی با استفاده از نرم افزار متلب طراحی شده است. نتایج شبیه سازی ها عملکرد کنترل کننده را برای سیستم کنترل هواپیما نشان می­دهند.  فیلتر کالمن موضوع گسترده ای در تحقیقات بوده است. به صورت کلی در حوزه ناوبری همزمان کاربرد دارد. برای مثال برای تعیین سرعت یک هواپیما یا زاویه سر خوردن آن (sideslip) یک مورد می توان از رادار دوپلر استفاده نمود. نشان های سرعت یک سیستم ناوبری داخلی یا اطلاعات بادی در سیستم داده هوا باشد.  ترجیحا با نادیده گرفتن این خروجی ها، یک فیلتر کالمن می تواند برای ترکیب این داده و دانش دینامیک های سیستم گوناگون برای تولید یک تخمین زوایای sideslip,roll,pitch استفاده شود.

Abstract
This paper, describes a LQG and LQR robust controller for the lateral and longitudinal flight dynamics of an aircraft control system. The controller is used in order to achieve robust stability and good dynamic performance against the variation of aircraft parameters. The application of the proposed LQG and LQR robust control scheme is implemented through the simulation. The proposed robust controller for aircraft stability is designed using Matlab/Simulink program. Simulation results confirm the performance of the proposed controller for aircraft control system. Since the time of its introduction, the Kalman filter has been the subject of extensive research and
application, particularly in the area of autonomous or assisted navigation. For example, to determine the velocity of an aircraft or sideslip angle, one could use a Doppler radar, the velocity indications of an inertial navigation system, or the relative wind information in the air data system. Rather than ignore any of these outputs, a Kalman filter could be built to combine all of this data and knowledge of the various systems dynamics to generate an overall best estimate of pitch, roll and sideslip angle

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کد c14:

سال انتشار 2010  

عنوان مقاله:

MIMO adaptive fuzzy terminal sliding-mode controller for robotic manipulators

چکیده مقاله:

A new design approach of a multiple-input–multiple-output (MIMO) adaptive fuzzy terminal sliding-mode controller (AFTSMC) for robotic manipulators is described in this article. A terminal sliding-mode controller (TSMC) can drive system tracking error to converge to zero in finite time. The AFTSMC, incorporating the fuzzy logic controller (FLC), the TSMC, and an adaptive scheme, is designed to retain the advantages of the TSMC while reducing the chattering. The adaptive law is designed on the basis of the Lyapunov stability criterion. The self-tuning parameters are adapted online to improve the performance of the fuzzy terminal sliding-mode controller (FTSMC). Thus, it does not require detailed system parameters for the presented AFTSMC. The simulation results demonstrate that the MIMO AFTSMC can provide a reasonable tracking performance

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کد c15:

سال انتشار 2009

عنوان مقاله:

An efficient multi-objective model predictive control framework of a PEM fuel cell

چهارچوب کنترلی مدل پیش بین چند هدفه برای سلول سوختی PEM

چکیده مقاله:

سلولهای سوختی که برای تولید انرژی پاک به کار گرفته می شوند، توجه بسیاری از مراکز پژوهشی و صنعتی را در سالهای اخیر به خود جلب کرده اند. مدل دینامیکی براساس دادههای حاصل از تست عملی برای سلولهای سوختی تعریف و اعتبارسنجی شده است. دادههای عملی به کار رفته در استخراج مدل، براساس شرایط کاری مختلف )دما و فشار بالا، تغییرات ولتاژ و جریان و …( جمع آوری شده اند. در این مقاله، چهارچوب مجتمعی که شامل الگوریتم پیشبینی بیشینه توان به صورت آنلاین و یک مدل غیرخطی میباشد، ارائه شده است.چهارچوب پیشنهادی با هدف نگهداری سلول در نقطهای نزدیک به توان بهینه طراحی شده است. شبیه سازی های نشان می دهد که چهارچوب پیشنهادی، منتج به بهبود عملکرد با در نظر گرفتن بازدهی و عملکرد ایمن سلول سوختی تحت شرایط کاری متنوع می شود.

Abstract: Fuel cell systems can produce clean energy and have attracted the interest of both industrial and basic research in the recent years. They are part of a promising benign and environmentally friendly technology and they can be used both in mobile and stationary applications. A dynamic model was constructed and validated using experimental data based on a specific application, consisting of a high temperature PEM Fuel Cell (FC) working at a constant pressure and a Power Conversion Device that controls the current drawn from the FC. An integrated framework that consists of an online maximum power point prediction algorithm and a non-linear model based control scheme is presented. The proposed framework aims to maintain the fuel cell close to the optimum power point and the corresponding oxygen excess ratio level. Simulation studies show that the proposed control framework results in improved performance regarding the efficient and safe fuel cell operation under varying operating conditions
Keywords: fuel cell control, model predictive control, power management

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کد c17:

سال انتشار 2006

عنوان مقاله:

Discrete-Time Average-Consensus under Switching Network Topologies

تجمیع متوسط زمان گسسته تحت توپولوژی شبکه های سوئیچینگ

چکیده مقاله:

در این مقاله یک الگوریتم توزیع شده برای تجمیع متوسط (Average Consensus) در چهارچوب زمان گسسته (Discrete Time) براساس تعریف حد ماتریس قراردادی تجمیع متوسط، ارائه شده است. با استفاده از این الگوریتم، مسئله تجمیع متوسط تحت توپولوژی شبکه­های سوئیچینگ حل می­شود. سوئیچینگ شبکه به صورت لحظه­ای و متوازن انجام می­شود. به عبارت دیگر، اگر شبکه در یک لحظه بالانس باشد و پیوند گراف­ها هر T ثانیه برقرار شود، تجمیع متوسط حاصل می شود. ماحصل این آنالیز، ایده تجمیع مرده است که به معنی تجمیع عوامل (agent) در زمان محدود و به طور متناوب است.

Abstract—This paper develops a distributed algorithm for average-consensus in a discrete-time framework based on a formal matrix limit definition of average-consensus. Using this algorithm, the average-consensus problem is solved under switching network topologies provided that the network switch between instantaneously balanced, connected-over-time networks. In other words, if at each instant the network is balanced and the union of graphs over every interval T is connected, then average-consensus can be achieved. An interesting product of this analysis is the notion of “deadbeat” consensus where a system of agents achieves consensus (average or otherwise) in finite time rather than asymptotically

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کدc18:

سال انتشار 2007

عنوان مقاله:

An Application of Active Disturbance Rejection Control to Self-Sensing Magnetic Bearings

دستگاه کنترل حذف اغتشاش فعال برای خود کنترلی یاتاقانهای مغناطیسی

چکیده مقاله:

یک مدل خطی خود سنجی یاتاقان مغناطیسی مورد استفاده در یک دستگاه ذخیره انرژی فلایول (چرخ طیار) تجزیه تحلیل شده و یک مکانیسم بازخورد درونی شناسایی شد. بر اساس این مدل، کنترلر حلقه آبشاری با استفاده از یک روش طراحی کنترل جدید طراحی میگردد که به طور فعال اغتشاشات خارجی را حذف کرده و از مکانیسم بازخورد استفاده میکند. نتایج شبیه سازی عملکرد حذف اغتشاش نیرو ارائه می شود. یاتاقانهای مغناطیسی برای تعلیق غیر تماسی روتور چرخ طیار استفاده شده است و از این روی موجب برطرف شدن مسائل اصطکاک و فرسودگی مرتبط با دستگاههای با سرعت بالا که از یاتاقانهای مکانیکی استفاده می کنند، می شود. تعلیق از طریق یک مجموعهای از آهنرباهای الکتریکی حاصل میشود که بین آنها روتور واقع شده است.

Abstract—A linearized model of a self-sensing magnetic bearing used in a flywheel energy storage application is analyzed, and an intrinsic feedback mechanism is identified. Based on the model, a cascaded-loop controller is designed using a novel control design technique which actively rejects external disturbances, taking advantage of the feedback mechanism. Simulation results of force-disturbance rejection performance are presented

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کد c19:

مقاله فارسی است.

عنوان مقاله:

اجرای فرایند فرود خودکار هواپیما با کنترل کننده فازی

چکیده مقاله:

در این مقاله یک روش جدید مبتنی بر سیستم های فازی برای کننرل پروسه فرود خودکار هواپیما طراحی شده است. پروسه فرود هواپیما یک پروسه پیچیده و ناپایدار می باشد و به شدت نیازمند طراحی یک کنترلر قابل اعتماد و پایدار ساز می باشد. سیستم های فازی به عنوان تقریب گرهای عمومی شناخته می شوند، بنابراین با استفاده از این نوع کنترلرها می توان کنترلری با هر دقت دلخواه برای کنترل خودکار فرود هواپیما طراحی نمود. برای بررسی کارایی روش ارائه شده از مدل هواپیمای HL20 ارائه شده در متلب برای شبیه سازی و ارزیابی استفاده شده است؛ که نتیجه آن سادهتر و سریعتر بودن کنترلر است.

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کد c20:

سال انتشار 2011

عنوان مقاله:

Adaptive Attitude Control for a Small Satellite with Integrated Singularity Avoidance and Momentum Management

کنترل وضعیت تطبیقی برای یک ماهواره کوچک با مدیریت تکانه و اجتناب از تکین ( منفرد)

چکیده مقاله:

Abstract—An adaptive attitude controller for a small satellite utilizing variable speed control moment gyroscopes (VSCMGs) is proposed, which performs integrated singularity avoidance and momentum management using null motion. An adaptive controller yields accurate attitude tracking while the VSCMG null motion achieves singularity avoidance and momentum management. The proposed controller compensates for parametric uncertainties present in the nonlinear satellite dynamics. Asymptotic attitude tracking and exponential momentum tracking are proven via Lyapunov stability analysis. Simulation results indicate the performance of the proposed controller as a VSCMG steering law

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کد c21:

سال انتشار 2015

عنوان مقاله:

Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique

بهینه سازی یک الگوریتم MPPT مبتنی بر کنترل منطق فازی توسط تکنیک بهینه سازی ازدحام ذرات

چکیده مقاله:

Abstract: In this paper, an asymmetrical fuzzy-logic-control (FLC)-based maximum power point tracking (MPPT) algorithm for photovoltaic (PV) systems is presented. Two membership function (MF) design methodologies that can improve the effectiveness of the proposed asymmetrical FLC-based MPPT methods are then proposed. The first method can quickly determine the input MF setting values via the power–voltage (P–V) curve of solar cells under standard test conditions (STC). The second method uses the particle swarm optimization (PSO) technique to optimize the input MF setting values. Because the PSO approach must target and optimize a cost function, a cost function design methodology that meets the performance requirements of practical photovoltaic generation systems (PGSs) is also proposed. According to the simulated and experimental results, the proposed asymmetrical FLC-based MPPT method has the highest fitness value, therefore, it can successfully address the tracking speed/tracking accuracy dilemma compared with the traditional perturb and observe (P&O) and symmetrical FLC-based MPPT algorithms can improve the transient time and the MPPT tracking accuracy by 25.8% and 0.98% under STC, respectively

Keywords: fuzzy logic control; maximum power point tracking; particle swarm optimizationCompared to the conventional FLC-based MPPT method, the obtained optimal asymmetrical

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کد c22:

سال انتشار 2016

عنوان مقاله:

Optimization of fuzzy controller design using a new bee colony algorithm with fuzzy dynamic parameter adaptation

بهینه سازی طراحی کنترل کننده فازی توسط یک الگوریتم کولونی زنبور عسل جدید به همراه انطباق پارامتر دینامیکی فازی

چکیده مقاله:

In this paper we are presenting a modification of a bio-inspired algorithm based on the bee behavior (BCO,bee colony optimization) for optimizing fuzzy controllers. BCO is a metaheuristic technique inspired bythe behavior presented by bees in nature, which can be used for solving optimization problems. First,the traditional BCO is tested with the optimization of fuzzy controllers. Second, a modification of theoriginal method is presented by including fuzzy logic to dynamically change the main parameter valuesof the algorithm during execution. Third, the proposed modification of the BCO algorithm with the fuzzyapproach is used to optimize benchmark control problems. The comparison of results show that theproposed fuzzy BCO method outperforms the traditional BCO in the optimal design of fuzzy controllers

Keywords: Fuzzy logic, Fuzzy controller, Linguistic variables, BCO, FBCO, Dynamic parameter adjustment

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کد c23:

سال انتشار 2010

عنوان مقاله:

An Interval Fuzzy Controller for Vehicle Active Suspension Systems

یک کنترل کننده فازی فاصله ای برای سیستم های تعلیق اکتیو خودرو

چکیده مقاله:

Abstract—A novel interval type-2 fuzzy controller architecture is proposed to resolve nonlinear control problems of vehicle active suspension systems. It integrates the Takagi–Sugeno (T–S) fuzzy model, interval type-2 fuzzy reasoning, the Wu–Mendel uncertainty bound method, and selected optimization algorithms together to construct the switching routes between generated linear model control surfaces. The stability analysis of the proposed approach is presented. The proposed method is implemented into a numerical example and a case study on a nonlinear half-vehicle active suspension system. The simulation results demonstrate the effectiveness and efficiency of the proposed approach

Index Terms—Active suspension system, interval type-2 fuzzy control, stability analysis

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کد c24:

سال انتشار 2010

عنوان مقاله:

Adaptive synchronization of uncertain Rössler hyperchaotic system based on parameter identification

سنکرون سازی انطباقی یک سیستم فوق اشوب نامطمین راسلر بر اساس شناسایی پارامتر

چکیده مقاله:

Abstract
In this Letter, an approach of adaptive synchronization and parameters identification of uncertain Rössler hyperchaotic system is proposed. The suggested tool proves to be globally and asymptotically stable by means of Lyapunov method. With this new and effective method, parameters identification and synchronization of Rössler hyperchaotic with all the system parameters unknown, can be achieved simultaneously. Theoretical proof and numerical simulation demonstrate the effectiveness and feasibility of the proposed technique
Keywords: Synchronization; Parameters identification; Hyperchaotic system

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کد c25:

سال انتشار 2013

عنوان مقاله:

Controlling of D.C. Motor using Fuzzy Logic Controller

کنترل موتور DC توسط کنترل کننده فازی

چکیده مقاله:

Abstract: Most of the industrial controllers in use today utilize PID controllers. In this paper four methods for tuning of a PID controller are compared. A mathematical model of the most commonly used dynamic system i.e., a d.c. motor is derived and a PID controller is used in conjunction to it. Ziegler-Nichols rule based on the value of Kp is used to tune the PID controller and the response is studied. Further, fuzzy controller is used with PID i.e. Fuzzy PID Controller. The results obtained are compared and a conclusion is drawn that Fuzzy controlled PID responds better in case of change in load and other system disturbances

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کد c26:

سال انتشار 2017

عنوان مقاله:

An optimal general type-2 fuzzy controller for Urban Traffic Network

یک کنترل کننده فازی نوع 2 جامع بهینه برای شبکه ترافیک شهری

چکیده مقاله:

Abstract: Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles. In this study, a combination of the general type-2 fuzzy logic sets and the Modified Backtracking Search Algorithm (MBSA) techniques are used in order to control the traffic signal scheduling and phase succession so as to guarantee a smooth flow of traffic with the least wait times and average queue length. The parameters of input and output membership functions are optimized simultaneously by the novel heuristic algorithm MBSA. A comparison is made between the achieved results with those of optimal and conventional type-1 fuzzy logic controllers

Keywords: Traffic Signal Control , Optimal General Type-2 Fuzzy Controller (OGT2FC) , Modified Backtracking Search Algorithm MBSA

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کد c27:

سال انتشار 2015

عنوان مقاله:

A novel multistage Support Vector Machine based approach for Li ion battery remaining useful life estimation

روشی مبتنی بر یک ماشین برداری حمایتی چندحالته جدید برای تخمین عمر مفید باقی مانده باتری لیتیوم یون

چکیده مقاله:

Abstract
Real-time prediction of remaining useful life (RUL) is an essential feature of a robust battery management system (BMS). In this work, a novel method for real-time RUL estimation of Li ion batteries is proposed that integrates classification and regression attributes of Support Vector (SV) based machine learning technique. Cycling data of Li-ion batteries under different operating conditions are analyzed, and the critical features are extracted from the voltage and temperature profiles. The classification and regression models for RUL are built based on the critical features using Support Vector Machine (SVM). The classification model provides a gross estimation, and the Support Vector Regression (SVR) is used to predict the accurate RUL if the battery is close to the end of life (EOL). By the critical feature extraction and the multistage approach, accurate RUL prediction of multiple batteries is accomplished simultaneously, making the proposed method generic in nature. In addition to accuracy, the multistage approach results in faster computations, and hence a trained model can potentially be used for real-time onboard RUL estimation for electric vehicle battery packs

Keywords: Remaining Useful Life , Classification , Regression , Support Vector Machine , Battery life models

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