Seyed Sadati - Academia.edu (original) (raw)

Papers by Seyed Sadati

International Journal of Mathematical and Computational Sciences, Nov 15, 2021

Bayesian approach can be used for parameter identification and extraction in state space models a... more Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained.

InTech eBooks, Mar 1, 2010

The International Journal of Multiphysics, 2010

In this chapter, firstly, the pump-displacement-controlled actuator system with applications in a... more In this chapter, firstly, the pump-displacement-controlled actuator system with applications in aerospace industries is modeled using the bond graph methodology. Secondly, an approach is developed towards simplification and model order reduction for bond graph models that can usually use in conceptual representation or design procedures. The model order reduction process indicates which system components have the most bearing on the frequency response, and the final model retains structural information. Finally, the state space form of mathematical model of the system based on the bond graph model is presented. By associating bond graph model, it becomes possible to design fault detection and isolation (FDI) algorithms, i.e. the generation of fault indicators, and to improve monitoring of the actuator.

In this article, speed control of a servo hydraulic rotary actuator is investigated, using flexib... more In this article, speed control of a servo hydraulic rotary actuator is investigated, using flexible structure neural network (NN). The applied architecture of NN is a feedback error learning (FEL), whose underlying learning strategy is based on the inverse dynamics of the system under control. The classic control output was taken as the cost function to be minimized by the NN. A three-layer feedforward NN was applied and a flexible sigmoid activation function was used for the hidden layer nodes. The learning paradigm was online, making use of the back propagation of error with momentum. A simulation was performed and the results obtained indicated the high capability of the flexible NN in learning inverse dynamics in real time in controlling servo hydraulic systems.

Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditi... more Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the future behavior of the overtaking vehicle in real traffic flow. In these models, the kinematic features of Driver-Vehicle-Units (DVUs) such as distance, velocity, and acceleration are used. Unlike the previous models, where some variables of the two involved vehicles are considered to be constant, in this paper, instantaneous values of the variables are considered. The first model predicts the future value of the longitudinal acceleration and the movement angle of the overtaking vehicle. The other model predicts the overtaking trajectory for the overtaking vehicle. The second model is designed for two different vehicle classes: motorcycles and autos. Also, the result of the trajectory prediction model is compared with the result of other models. This comparison provides a better chance to analyze the performance of this model. Using the field data, the outputs of the MANFIS models are validated and compared with the real traffic dataset. The simulation results show that these two MANFIS models have a very close compatibility with the field data and reflect the situation of the traffic flow in a more realistic way. These models can be used for all types of drivers and vehicles and also in other roads and are not limited to certain types of situations. The proposed models can be employed in ITS applications and the like.

The International Journal of Advanced Manufacturing Technology, 2007

In this article the results of the application of a flexible structure artificial neural network ... more In this article the results of the application of a flexible structure artificial neural network for controlling the angular velocity of a servo-hydraulic rotary actuator are discussed. A mathematical model for the system is derived, and a flexible artificial neural network (ANN)-based controller with the feedback error learning method as a learning algorithm is applied to the system. The neural network-based controller has a feed-forward structure and three layers. The flexible bipolar sigmoid function was used as the activation function of the network. The simulation and experimental results show good performance of the developed method in learning the inverse dynamic of the system and controlling the angular velocity of the rotary hydro motor. The advantages of the developed method for servo-hydraulic actuators over other traditional approaches are discussed.

This study proposed a new method for control cooperating robots. Many researchers have touched th... more This study proposed a new method for control cooperating robots. Many researchers have touched the problem of controlling an array of mobile robots. These controllers have been applied to different kinds of mobile robots. These robots are highly capable in industry due to their low cost and simplicity. Through their simple geometry, they showed to be an appropriate choice for varieties of applications. However, the presence of non-holonomic constraints in their motion renders the control of this robot quite a challenging issue. Conditions for which mobile robots are designed for include many uncertainties since these robots are employed in environments unknown to the robot and hence the robot may be experiencing the workspace for the first time. In other words, the robot may not have been in a similar situation before. In addition, in actual applications, the robot normally suffers from noise and perturbations inflicted upon its control system, making it extremely important to desig...

International Journal of Applied Mechanics and Engineering, 2010

Reliable object detection is one of the most important requirements of environment perception in ... more Reliable object detection is one of the most important requirements of environment perception in autonomous driving. The goal of this research is to find a convenient solution to detect objects in images from the self-driving car medium. Convolutional neural networks (CNNs) are deep neural networks used in image processing, object classification, and object recognition. Therefore, deep convolution networks are employed in this project to identify objects accurately. In order to train and evaluate the neural network, we used BDD100K dataset which is one of the largest open-source datasets in autonomous driving published by Berkeley University. The approach used in the proposed algorithm is to apply the feature pyramid network along with a single-stage object detector, which enhances the accuracy of object detection. In addition, it improves the detection of different scales, especially small ones compared to those of the previous works, leading to increased safety and security in self-driving cars.

Asian Journal of Control, Feb 4, 2016

Quasi-periodic and chaotic behavior, along with the control of chaos for a Gyrostat satellite (GS... more Quasi-periodic and chaotic behavior, along with the control of chaos for a Gyrostat satellite (GS), is investigated in this work. The quaternion-based dynamical model of the GS is first derived, and then the influences of the reaction wheels in the GS structure, under the gravity gradient perturbation that causes a route to chaos through quasi-periodicity mechanism, is investigated. For the suppression of chaos in the system, a chaos control system with the quaternion feedback is designed for the GS based on the extension of the Ott-Grebogi-Yorke (OGY) method using the linearization of the Poincaré map. In the extended OGY controller, the Poincaré map is estimated using the Least Square Support Vector Machine (LSSVM) technique. After linearization of the Poincaré map, the Discrete-time Linear Quadratic Regulator (DLQR) is applied on the linearized Poincaré map, making the DLQR-OGY controller for chaos. The DLQR-OGY control system stabilizes the orbits to the fixed points providing a small control input signal, which leads to a decrease in the control effort and energy consumption in the GS system.

Structural Engineering and Mechanics, Dec 20, 2009

In this paper a free-free uniform beam with damping effects subjected to follower and transversal... more In this paper a free-free uniform beam with damping effects subjected to follower and transversal forces at its end is considered as a model for a space structure. The effect of damping on the stability of the system is first investigated and the effects of the follower and transversal forces on the vibration of the beam are shown next. Proportional damping model is used in this work, hence, the effects of both internal (material) and external (viscous fluid) damping on the system are noted. In order to derive the frequency of the system, the Ritz method has been used. The mode shapes of the system must therefore be extracted. The Newmark method is utilized in the study of the system vibration. The results show that an increase in the follower and transversal forces leads to an increase of the vibrational motion of the beam which is not desirable.

An optimal guidance law for a missile flight is one which determines appropriate controls to prod... more An optimal guidance law for a missile flight is one which determines appropriate controls to produce a flight path such that some mission objective will be achieved in the most efficient manner. Optimal Control Theory is often used to accomplish this task. One must bear in mind, however, that the usefulness of optimal control is sharply divided between two distinct classes of dynamical systems, namely, linear systems and nonlinear systems. For linear systems, the theory is complete in the sense that given a quadratic cost, a closed-loop feedback guidance law may be determined. For nonlinear systems, generally the best one can do is to determine an open-loop guidance law numerically using a software package such as MISER (1). (Some notable exceptions exist where a complete analytical synthesis of the closed-loop control may be obtained for nonlinear systems, e.g., in (2).) Although open-loop optimal guidance laws for nonlinear systems can now be computed quite efficiently with the advances of sophisticated numerical techniques along with high-speed digital computers, the highly-nonlinear and complex dynamics of missiles precludes the possibility of on-line implementation of open-loop optimal control. It has always been realized that if optimal closed-loop solutions could be obtained for comprehensive nonlinear systems such as missiles, then guidance laws based on such results would be superior to any other guidance laws available today. This superiority is due to, among other things, the elimination of some of the restrictive, and in many cases unrealistic assumptions made in the derivation of most current guidance laws in use such as, for instance, "tail-chase", unbounded control, simplified dynamics and/or aerodynamics, and non-maneuvering target, to name a few. In this study, an optimal closed-loop control law is obtained off-line by means of a Neural Network which is then used as an on-line controller for a generic missile. In the nonlinear case, the missile/target scenario is set up as a mathematical model using realistic dynamics. Then, given a Performance Index, the open-loop control is obtained by solving the problem using the optimal control software MISER for a number of different initial configurations. These open-loop solutions are then used to "teach" a neural network via backpropagation. Through simulation, it is then demonstrated how well the neural network performs as a feedback controller. The miss distance as well as the value of the Performance Index are used as measures of performance to be compared under the original open-loop control and the neural network closed-loop control. This problem is further extended to include a time lag in the missile dynamics. The effect of this time delay in the overall performance of the optimal controller is then examined

Proceedings Of The Institution Of Mechanical Engineers, Part K: Journal Of Multi-body Dynamics, Oct 4, 2013

The chaotic dynamics of roto-translatory motion of a triaxial Kelvin-type gyrostat satellite unde... more The chaotic dynamics of roto-translatory motion of a triaxial Kelvin-type gyrostat satellite under gravity gradient perturbations is considered. The Hamiltonian approach is used for modelling of the coupled spin-orbit equations of motion. The complex Hamiltonian of the system is reduced via the extended Deprit canonical transformation using the Serret-Andoyer variables. Therefore, this reduction leads to the derivation of the perturbation form of the Hamiltonian that can be used in the Ricci curvature criterion based on the Riemannian manifold geometry for the analysis of chaos phenomenon. The results obtained from Ricci method as well as the values from the Lyapunov exponent demonstrate the presence of a strange attraction and chaotic responses in the perturbed system. The simulation results based on numerical methods such as Poincaré section, trajectories of phase portrait and time series responses quantitatively confirm the heteroclinic bifurcation and chaotic behaviour in the rotational–translational dynamics of the gyrostat satellite system.

هلاقم تاعلاطا هدیکچ لماک یشهوژپ هلاقم :تفایرد 28 یدرورف ن 1396 :شریذپ 20 ادرخ د 1396 :تیاس رد هئا... more هلاقم تاعلاطا هدیکچ لماک یشهوژپ هلاقم :تفایرد 28 یدرورف ن 1396 :شریذپ 20 ادرخ د 1396 :تیاس رد هئارا 29 ریت 1693 یشان هبذاج نایدارگ یشاشتغا رواتشگ ریثات تحت بلص هراوهام کی تیعضو کیمانید رد بوشآ هدیدپ یددع و یلیلحت یسررب هب ،هلاقم نیا رد یم یوضیب رادم کی رد تکرح زا تابثا فده ،یلیلحت شخب رد .میزادرپ دوجو هب سپس و بوشآ هطبار ندروآ تسد بوشآ هیحان ضرع یارب یا رب هب تیساسح و هراکناوپ تشاگن یددع شور ود کمک اب یلیلحت شخب یجنسرابتعا فده ،یددع شخب رد .تسا متسیس یاهرتماراپ ساسا یم جارختسا شاشتغا نودب متسیس نینوتلیمه ادتبا راک نیا یارب .تسا هیلوا طیارش یمه نیا .دوش راد نینوتل ا رد نیا .تسا یدازآ هجرد هس ی اب و تکرح تباث ود نیا زا هدافتسا اب .تسا متنمم و یژرنا لماش تکرح تباث ود یاراد شاشتغا نودب تلاح رد تیعضو کیمانید هک تسا یلاح ترس لاکینوناک لیدبت کمک ی هب لیدبت و هدش هداد هبترم شهاک شاشتغا نودب متسیس نینوتلیمه ،ریودنآ یدازآ هجرد کی متسیس ک یم رب یوضیب رادم رد تکرح رطاخ هب هبذاج نایدارگ زا یشان تاشاشتغا ،همادا رد .دوش ترس یاهریغتم ساسا هدز نیمخت نامز و ریودنآ یم هداس و نیمخت نیا هجیتن رد .دوش یم...

Driver’s error contributes to over 75 percent of road crashes especially in overtaking maneuvers.... more Driver’s error contributes to over 75 percent of road crashes especially in overtaking maneuvers. Intelligent transport systems (ITS) are under active development worldwide as a means of reducing loss of life. Since overtaking maneuver is a complex maneuver and so many factors affect it, the automation of this maneuver has been considered to be one of the toughest challenges in the development of autonomous vehicles. Extremely nonlinear nature of Overtaking behavior asks for the development of intelligent algorithms to describe, model and control this phenomenon. Uncertainties and inaccuracies, intervention of judgments and human logic in controlling the vehicle, necessitates use of intelligent control methods based on soft computing techniques like neural network and fuzzy logic systems. Integration of human expert knowledge, and learning based on data, are powerful tools enabling fuzzy systems to deal with nonlinear nature of driving behaviors. Usually, classic control methods are...

Energy Conversion and Management, 2021

Abstract Today, the international community is obligated to utilize renewable energy due to accel... more Abstract Today, the international community is obligated to utilize renewable energy due to accelerated energy consumption on the one hand and the necessity of environmental pollution reduction, on the other hand. Meanwhile, the Solar Power Tower (SPT) is at significantly optimum conditions for integration with conventional fossil power plants due to reaching temperatures of up to 1200 °C and a high-power generation capacity. The present paper demonstrates the optimal layout of the new hybrid-cycle power generation section with SPT. The Heliostat field was optimized as a transient optical model at all hours of the year by considering the city of Seville as a case study using the System Advisor Model (SAM). Subsequently, the cycle’s thermo-economic model was developed using Engineering Equation Solver (EES) to minimize the Levelized Cost Of Electricity (LCOE). In the following, four fluids of n-Butane, R245fa, n-Pentane, and R123 were utilized for the final analysis as a downstream fluid. Through this process, the appropriate operating fluid was selected. The study results demonstrate an increase in the efficiency of the novel proposed cycle layout compared to a solar power tower power plant with standard pressurized air-fluid; moreover, it reduced fuel consumption, CO2 emission, and LCOE. The maximum efficiency and the minimum LCOE were53.25% and 61.8 $ / M W h , respectively. The n-Pentane fluid was recognized as the most appropriate fluid for the downstream cycle. Due to the optimization of solar parts, the number of heliostat field mirrors were 889, with a total area of 131,525 m 2 and a central tower height of 105.87 m . The novel presented cycle layout solves a portion of the pressurized air receiver limitations, enabling access to higher efficiency and lower LCOE with the real payback time (RPBT) of 3.876 years, the annual solar share of 23.1%, and reduction of CO2 production by 33,426 t o n / y e a r . Consequently, this study’s proposed cycle layout signifies a promising future for using SPT with high efficiency and better environmental and economic conditions.

Structural Engineering and Mechanics, 2009

Structural Engineering and Mechanics, 2013

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