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 و ایمیل جهت سفارش

09027952876

tarjomehrooz@gmail.com

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http://www.telegram.me/tarjomehrooz



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 residual (tracking 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 aimed
at 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.

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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 میشوند، 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 …( جمعآوری 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. شبیهسازیهای نشان میدهد که چهارچوب پیشنهادی، منتج به بهبود عملکرد با در نظر گرفتن بازدهی و عملکرد ایمن سلول سوختی تحت شرایط کاری متنوع می شود.

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