Novel Method for Improving the Capacity of Optical MIMO System Using MGDM

In current local area networks, multimode fibers (MMFs), primarily graded index (GI) MMFs, are the main types of fibers employed for data communications. Due to their enormous bandwidth, it is considered that they are the main channel medium that can offer broadband multiservices using optical multiplexing techniques. Amongst these, mode group diversity multiplexing (MGDM) has been proposed as a way to integrate various services over an MMF network by exciting different groups of modes that can be used as independent and parallel communication channels. In this paper, we study optical multiple-input–multiple-output (O-MIMO) systems using MGDM techniques while also optimizing the launching conditions of light at the fiber inputs and the spot size, radial offset, angular offset, wavelength, and the radii of the segment areas of the detectors. We propose a new approach based on the optimization of launching and detection conditions in order to increase the capacity of an O-MIMO link using the MGDM technique. We propose a (3 $times$ 3) O-MIMO system, where our simulation results show significant improvement in GI MMFs' capacity compared with existing O-MIMO systems. Optical multiple-input-multiple-output multiplexing of parallel communication multichannels over a single multimode fiber network. Optical multiple-input-multiple-output multiplexing of parallel communication multichannels over a single multimode fiber network

Water status and yield response to deficit irrigation and fertilization of three olive oil cultivars under the semi-arid conditions of Tunisia

Sustainability of olive production is possible by adopting the modern techniques of irrigation and fertilization. In Tunisia, olive trees are usually cultivated in poor soils, under semi-arid conditions characterized by water scarcity. This study investigated the effects of different water supply and fertilization on leaf water status and crop yield of three different olive oil varieties cultivated in central Tunisia, during four experimental seasons (2014-2017). Three treatments were examined: trees conducted under rainfed conditions (TRF), which represented the control treatment, trees irrigated with 50% ETc (T50) and, finally, trees irrigated with 50% ETc and with additional fertilization (T50F). Leaf water content and potential, yield and water use efficiency have been monitored on three different varieties, Chetoui, Chemlali, and Koroneiki, which are quite typical in the considered region. For all the growing seasons, midday leaf water potentials were measured from April to September. Midday leaf water potentials (MLWP) were generally higher for the two irrigated treatments (T50 and T50F) than for non-irrigated trees (TRF). As the season proceeded, MLWPs tended to decrease during summer for all the treatments and varieties. The lowest values were observed for the non-irrigated trees, varying between -3.25 MPa to -4.75 MPa. Relative leaf water content followed the same trends of midday leaf water potentials. Chetoui showed the lowest yield, which did not exceed 1530 Kg/(ha year), even for irrigated and fertilized trees. On the other hand, the yields of Chemlali and Koroneiki, cumulated in the four years, reached the maximum value of about 20 tons/ha. For these two varieties, the cumulated yield obtained in the control treatment (TRF) resulted significantly lower than the corresponding of the other two treatments (T50 and T50F). The highest irrigation water use efficiency (WUE) was estimated for Chemlali (T50) and (TRF). WUE was equal to 1.22 Kg/m3 for Koroneiki under fertigated treatment (T50F). Application of the only water supply (50% ETc) or associated with fertilizer improved the tree water status and increased the productivity of Chemlali and Koroneiki varieties

Nanoparticles Decorated on Resin Particles and Their Flame Retardancy Behavior for Polymer Composites

New nanocomposites have been developed by doping of amberlite IR120 resin with spherical TiO2 nanoparticles in the presence of maleate diphosphate. Polystyrene composites of resin, maleate diphosphate, and resin-maleate diphosphate were prepared individually. This is in addition to preparation of polymer nanocomposites of polystyrene-resin doped TiO2 nanoparticles-maleate diphosphate. The flame retardancy and thermal stability properties of these developed polymer composites were evaluated. The inclusion of resin and resin doped nanoparticles improved the fire retardant behavior of polystyrene composites and enhanced their thermal stability. Synergistic behavior between flame retardant, resin, and nanoparticles was detected. The rate of burning of the polymer nanocomposites was recorded as 10.7 mm/min achieving 77% reduction compared to pure polystyrene (46.5 mm/min). The peak heat release rate (PHRR) of the new polymer composites has reduced achieving 46% reduction compared to blank polymer. The morphology and dispersion of nanoparticles on resin and in polymer nanocomposites were characterized using transmission and scanning electron microscopy, respectively. The flame retardancy and thermal properties were evaluated using UL94 flame chamber, cone tests, and thermogravimetric analysis, respectively

Fuzzy logic based robotic controller

Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed

Hysteresis phenomenon and multistability in figure-of-eight microstructured fiber laser

We report a theoretical investigation of multi-pulse emission of a microstructured figure-ofeight fiber laser operating in passive mode-locking. The proposed laser is mode locked by the nonlinear amplifying loop mirror (NALM). We study, in this paper, the hysteresis dependence and the number of pulses in steady state as a function of both the small signal gain and the nonlinear coefficient of microstructured fiber. The numerical simulation confirms that the pulse splitting is a consequence of the energy quantization in anomalous dispersion. Moreover, our results suggest that the hysteresis phenomenon is an intrinsic feature of the mode-locked fiber lasers independently of the exact mode-locking mechanism. Finally, we identify that the nonlinear coefficient of microstructured fiber plays a key role in the formation of multi-soliton

Genetic Algorithm Based Control System Design of a Self-Excited Induction Generator

This paper presents an application of the genetic algorithm (GA) for optimizing controller gains of the Self-Excited Induction Generator (SEIG) driven by the Wind Energy Conversion Scheme (WECS). The proposed genetic algorithm is introduced to adapt the integral gains of the conventional controllers of the active and reactive control loop of the system under study, where GA calculates the optimum value for the gains of the variables based on the best dynamic performance and a domain search of the integral gains. The proposed genetic algorithm is used to regulate the terminal voltage or reactive power control, by adjusting the self excitation, and to control the mechanical input power or active power control by adapting the blade angle of WECS, in order to adjust the stator frequency. The GA is used for optimizing these gains, for an active and reactive power loop, by solving the related optimization problem. The simulation results show a better dynamic performance using the GA than using the conventional PI controller for active and reactive control

Optimization of Passive and Hybrid Mode-locked Figure Eight Laser

In pulsed fiber laser using Q-switching or mode locking techniques, the choice of the different components and the management of linear and non linear parameters of the cavity, play a paramount role in the generation of stable ultra short pulses with high peak powers and low widths. In this paper, we focus on the operating process of mode locked fiber lasers especially passively and hybrid type Eight Fiber Lasers (8FLs). By modeling the light propagation within the two cavities, we describe the whole operating process of ultra short pulses generation. The interaction between the mode locking mechanism and nonlinear effects in fiber laser is also illustrated. We demonstrate enhancing non linear effects do not lead necessarily to better results. It depends on the type of mode locking techniques used. The highest and narrowest output pulses are obtained for specific values of the non linear parameters and the mean dispersion of the cavity

Control of the square pulse properties in figure-of-eight microstructured fiber laser

We numerically analyze the square pulse emission from a passively mode-locked figure-of-eight microstructured optical fiber laser. Numerical simulations demonstrate that the high nonlinearity of the microstructured fiber plays a key role in the output pulse duration. A dual-stage erbium-doped fiber amplifier has been used in the cavity. The first amplifier, localized in the nonlinear amplifying loop mirror, allows control of the pulse width, while the second amplifier in the unidirectional ring allows variation of the amplitude without affecting the pulse width. Our results give some physical insight to the square pulse formation and the generation of high-energy pulses. Our numerical model provides a general approach to control the properties of a square pulse, and hence could be of great importance for the design of practical high-energy fiber laser systems

Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers

This paper presents a powerful supervisory power system stabilizer (PSS) using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS). The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC)-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC) driven by a fixed fuzzy set (FFS) which has 49 rules. Both fuzzy logic controller (FLC) algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study

Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers

This paper presents a powerful supervisory power system stabilizer (PSS) using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS). The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC)-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC) driven by a fixed fuzzy set (FFS) which has 49 rules. Both fuzzy logic controller (FLC) algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study