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Modeling, Walking Pattern Generators and Adaptive Control of Biped Robot
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Biped robots have gained much attention for decades. A variety of researches has been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand the human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. Some challenges encountered in the design of biped robots are: (1) biped robots have unstable structures due to the passive joint located at the unilateral foot-ground contact. (2) They have different configuration when switching from walking phase to another. During the singlesupport phase, the robot is under-actuated, while turning into an over-actuated system during the double-support phase. (3) Biped robots have many degrees of freedom (DOFs). (4) Biped robots interact with different unknown environments. Therefore, this work attempts to investigate and resolve different issues encountered in dynamics, walking pattern generators and control of biped robots; the details as follows: • Dynamics Two walking patterns have been modeled using two well-known formulations: Lagrangian and the modified recursive Newton-Euler (N-E) formulations. The first walking pattern moves with 6 DOFs during the single support phase (SSP) changing its configuration with 7 DOFs during the double support phase (DSP) (the stance foot will move directly during the DSP). Whereas the other walking pattern has 6 DOFs during all walking phases (the SSP and the two sub-phases of the DSP); the stance foot will be fixed during the first sub-phase of the DSP. These two walking pattern are different in configuration and number of phases during the DSP. To resolve the problem of over-actuation, a linear transition function is proposed to ensure smooth transition for the biped from the SSP to the DSP and vice versa. If we assume ideal dynamic response, this strategy can resolve the discontinuity in input control torque and ground reaction forces. • Walking pattern generators Two methods have been used to generate walking patterns of biped mechanism which are (1) optimal control theory and (2) center of gravity (COG)-based model. Computational optimal control has been performed to investigate the effects of some imposed constraints on biped locomotion, such as enforcing swing foot to move level to the ground, hip motion with constant height etc. finite difference approach has been used to transcribe infinite dimensional optimal control problem into finite dimensional suboptimal control problem. Then parameter optimization has been used to get suboptimal trajectory of the biped with the imposing different constraints. In general, any artificially imposed constraint to biped locomotion can lead to increase in value of input control torques. On the other hand, suboptimal trajectory of biped robot during complete gait cycle had been accomplished with different cases such that continuous dynamic response occurs. Enforcing the biped locomotion to move with linear transition of zero-moment point (ZMP) during the DSP can lead to more energy consumption. Using the simple COG-based model, a comparative study has been conducted to generate continuous motion for COG of the biped; all these methods depend on linear pendulum model. It has been shown all these methods are equivalent. On the other hand, the effect of foot configuration has been investigated. Foot rotation can improve biped configuration at heel strike by controlling foot angle. In addition, foot motion with impact can give some freedom and uniform biped configuration compared with motion without impact. To compensate for the deviation of ZMP trajectory due to approximate model of the COG, a novel strategy has been proposed to satisfy kinematic and dynamic constraints, as well as singularity condition. A stable motion has been obtained for the target walking patterns. • Low-level control Two control schemes have been proposed based on dynamics formulations which are conventional adaptive control based on local approximation technique and Lagrangian formulation, and virtual decomposition control (VDC) based on local approximation technique and recursive N-E formulation. In the first approach (conventional control), a new representation of dynamic matrices has been coined which is computationally efficient than other representation (sparse-base representation, Kronecker product etc.). Controller structures for the SSP and the DSP have been designed in details. Since adaptive control assumes no prior knowledge of estimated weighting matrices; therefore, zero input control torques could be result in at the beginning of each phase. Consequently, discontinuous dynamic response could result. The VDC is an efficient tool for complex robotic system such as biped robot. Therefore each subsystem (link, joint) has been controlled using adaptive approximation–based VDC. A novel optimization technique has been used to deal with continuous dynamic response; however, using zero initial weighting matrices for estimation dynamic matrices and vectors could result in zero input control at beginning of each walking phases.

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Digital modeling and its technical variables in contemporary interior design
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The current research sheds light on an important aspect of the great and rapid development in the field of science and technology and modern manufacturing methods as a result of the scientific revolution resulting from the accelerated cognitive development, which prompted designers in general and interior design in particular to exploit and invest in digital technology and the development of digital control in the process of designing the industrial product for the purpose of creativity and innovation through these digital programs Digital models achieve the requirements and desires of the interior designer according to the creative skill using modern software with high efficiency And extreme accuracy that is consistent with the requirem

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Publication Date
Sat Jan 11 2025
Journal Name
Journal Of Robotics And Control (jrc)
Design and Implementation of a Backstepping Time Varying Sliding Mode Control for the Angular Velocity Control of a Hydraulic Rotary Actuator
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The Backstepping Sliding Mode Control is a control technique used for controlling nonlinear systems. In this paper, the performance of the backstepping sliding mode controller schemes for the angular velocity control for a rotary actuator of an angular velocity control system that utilizes a novel hydraulic flow control method called inlet throttling was investigated. For the angular velocity dynamic, a linear state feedback with suitable high gain is designed as the virtual controller, where steady state error can be made arbitrarily small according to the gain value. A time varying sliding variable is then selected based on the designed virtual controller. The resulting control design is robust, and the maximum error of the angular veloci

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
THE PORTRAIT OF THE ARTIST AS A ROBOT: A LITERARY LOOK AT E-POETRY
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This study examines the validity of e-poetry as an acceptable literary genre. The
thematic, stylistic and esthetic features of a selected number of e-poems produced by
poetry generators are analyzed for this purpose. The e-poems are then compared with a
number of works written by Dada poets in order to establish the literary merit of the
former.

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Multi-Dimensional Angle of Arrival Estimation by Circular Phased Adaptive Array Antennas
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In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus
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Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

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Publication Date
Thu Oct 01 2020
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Design of an adaptive state feedback controller for a magnetic levitation system
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This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Thermal Modeling of Solar Still Coupled with Heat Pipes and Experimental Validation
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Water is the basis of the existence of all kinds of life, so obtaining it with good quality represents a challenge to human existence and development especially in the desert and remote cities because these areas contain small populations and water purification requires great materials and huge amounts of fossil fuels resulting pollution of the environment. Cheap and environmentally friendly desalination methods have been done by using solar distillations. Passive solar stills have low yields, so in this research, the problem is overcome by connecting four heat pipes which are installed on the parabolic concentrator reflector with passive solar still to increase the temperature of hot water to more than 90°C, as a resul

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Publication Date
Mon Feb 01 2016
Journal Name
International Journal Of Transportation Engineering And Traffic System, Ijtets
Comparative Modeling of Pavement Surface Texture Variables Using ANN and SPSS Software
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The health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the world based on the availability of equipment’s, skilled technicians’ and funds. An attempt has been made in this investigation to model the surface macro texture measured from sand patch method (SPM), and the surface micro texture measured from out flow time (OFT) and British pendul

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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