This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

Sustainable development is launched through the interaction between the economy and natural resources and preserving them from exhaustion as well as the efficient management of natural and social resources and includes a diversified economic condition and thus is the focus of attention to the development of economic structures, which is intended to improve the level of human well-being by increasing its share in the necessary goods and services and their relationship With economic growth, which is the most important driver of economic transformation, because it reflects the ability of society and increasing its productive capabilities and investing in the optimal way Although the Iraqi economy is considered one of the diversified

The focus of this research revolves around the importance level of sialic acid in the reasoning of cases, including tumors and then evaluate the patient's response to treatment and its impact on the immune response there are a lot of evidence showing that parts Alkrbu ???????? in peptides sugary and glycoproteins play an important role in Alfalitin life and responsiveness

Fe, Co and Sb nanopowders were fruitfully prepared by electrical wire explosion method in Double distilled and de-ionized water (DDDW) media. The formation of iron, cobalt and antimony (FeCoSb) alloy nanopowder was monitored by X-ray diffraction. The x-ray diffraction pattern indicates that there are iron, cobalt and antimony peaks. Optical properties of this alloy nanoparticles were characterized by UV-Visible absorption spectra. The absorption peak position is shifted to the lower wavelengths when the current increases. That means the mean size of the nanoparticles controlled by changing the magnitude of the current. The surface morphological analysis is carried out by employing Scanning Electron Microscope (SEM). Particles with varies

Thin films of tin sulfide (SnS) were prepared by thermal evaporation technique on glass substrates, with thickness in the range of 100, 200 and 300nm and their physical properties were studied with appropriate techniques. The phase of the synthesized thin films was confirmed by X-ray diffraction analysis. Further, the crystallite size was calculated by Scherer formula and found to increase from 58 to 79 nm with increase of thickness. The obtained results were discussed in view of testing the suitability of SnS film as an absorber for the fabrication of low-cost and non toxic solar cell. For thickness, t=300nm, the films showed orthorhombic OR phase with a strong (111) preferred orientation. The films deposited with thickness < 200nm deviate

the structrual and mechanical properties of thin Ni films of different thicknesses deposited on coring glass substrate using lonbeam sputtering(IBS) technique under vacuum torr have been studied the TEM and electron