The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matrices are obtained by the Lyapunov-like design. Therefore, this work is focused function approximation-based control algorithms considering centralized and decentralized approaches. In this work, the following control algorithms are designed: (1) Adaptive hybrid regressor-approximation control. This work attempts to combine the features of both the regressor and the approximation techniques in adaptive control. The regressor technique is a powerful tool for adaptive control of the known structure of modeling while the approximation is useful for estimation of time-varying uncertainty. Therefore, this work proposes adaptive hybrid regressor and approximation control for robots in both free and constrained spaces. The control law consists of three terms: (i) regressor term for initial estimation of the known structure of the robot dynamics, e.g. inertia matrix, Coriolis and centripetal matrix and gravity vector, and (ii) approximation term for estimation of internal and external disturbances resulted from the inexact calculation of regressor matrix and unknown modeling of friction, etc, and (iii) robust term consists of switching sgn(.) function. The control law is designed based on updating the uncertain parameters and the weighting coefficients corresponding to regressor and approximation respectively with position/force tracking purposes. The proposed controller is stable in the sense of Lyapunov stability. (2) Decentralized adaptive partitioned approximation control. Partitioned approximation control is avoided in most decentralized control algorithms; however, it is essential to design feedforward control with improved tracking accuracy. As a result, this work is focused on decentralized adaptive partitioned approximation control for complex robotic systems using the orthogonal basis functions as strong approximators. In essence, the partitioned approximation technique is intrinsically decentralized with some modifications. The proposed decentralized control law consists of three terms: the partitioned approximation-based feedforward term that is necessary for precise tracking, the high gain-based feedback term, and the adaptive sliding gain-based term for compensation of modeling error. The passivity property is essential to prove the stability of local stability of the individual subsystem with guaranteed global stability. Simulation experiments on 2-link robot and 6-link biped robot are performed to prove the effectiveness of the proposed algorithms.
The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a
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The article examines the definition of the verb in the form of the imperative mood (imperative) _ general information about the verb in Russian .
A verb in Russian is one of the parts of speech that unify all parts of speech, expressing the meaning of action, movement, process in grammatical forms of time, type, mood, face and voice. The imperative mood is a grammatical feature of the verb expressed through several forms of the verb that urges someone to do things. In other words, imperative mood or (imperative) : - one of the single meaning of the form . The form of the imperative expresses a supplicatio
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Abstract
The aim of this research is to identify the effectiveness of thinking skills in developing the life skills of the students of the first Academic year, particularly the differences in life skills according to the variable of study specialization (human-scientific). To achieve the research objectives, the life skills scale was constructed on the classification of (WHO). The psychometric properties of the scale were examined. The validity of the scale, which is the final form of (60) items, was valid for measuring the life skills. The scale was then applied to the research sample of (112) students of the first year of the University of Bisha. The SPSS program processed
... Show MoreThe study aims to reach a common point that achieves a balance between two interests, which are generally in conflict with the public interest and the interest of the individual owner of private property, by extrapolating the provisions of the constitutional judiciary that include the protection of private property, and this protection extends to every right of financial value and is not limited to a specific type, but It included everything that can be estimated with money, as ownership is no longer an advantage for the owner, but rather has become a right for him and a social function. The tax is imposed on what is derived from it, but if there is a need to prejudice it, the conditions, limits and restrictions expressly stipulated in the
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Brain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining
... Show MoreObjectives: The present study aimed to assess the compulsion among health care providers during the pandemic of COVID-19.
Methodology: a descriptive design was used in the present study. This study was conducted from October 10th, 2020 through May 20th, 2021. The study was conducted on a probability (convenient) sample of 248 physicians and nurses who work at Baghdad Teaching hospital in Baghdad city. The instrument was used in this study is the COVID Stress Scale-Arabic version (CSS).
Results: The result of this study showed that 42 % of HCPs had moderate symptoms and 36% of them had mild compulsive symptoms, and
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