In this research paper,an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator(DFIG)based wind energy system has been proposed.The proposed strategy u...In this research paper,an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator(DFIG)based wind energy system has been proposed.The proposed strategy used the robust Fractional-Order(FO)Proportional-Integral(PI)control technique.The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits.It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness.The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization(MRFO)algorithm.During the optimization process,the FOPI controller’s parameters are assigned to be the decision variables whereas the objective function is the error racking that to be minimized.To prove the superiority of the MRFO algorithm,an empirical comparison study with the homologous particle swarm optimization and genetic algorithm is achieved.The obtained results proved the superiority of the introduced strategy in tracking and control performances against various conditions such as voltage dips and wind speed variation.展开更多
The research on Unmanned Aerial Vehicles(UAV)has intensified considerably thanks to the recent growth in the fields of advanced automatic control,artificial intelligence,and miniaturization.In this paper,a Grey Wolf O...The research on Unmanned Aerial Vehicles(UAV)has intensified considerably thanks to the recent growth in the fields of advanced automatic control,artificial intelligence,and miniaturization.In this paper,a Grey Wolf Optimization(GWO)algorithm is proposed and successfully applied to tune all effective parameters of Fast Terminal Sliding Mode(FTSM)controllers for a quadrotor UAV.A full control scheme is first established to deal with the coupled and underactuated dynamics of the drone.Controllers for altitude,attitude,and position dynamics become separately designed and tuned.To work around the repetitive and time-consuming trial-error-based procedures,all FTSM controllers’parameters for only altitude and attitude dynamics are systematically tuned thanks to the proposed GWO metaheuristic.Such a hard and complex tuning task is formulated as a nonlinear optimization problem under operational constraints.The performance and robustness of the GWO-based control strategy are compared to those based on homologous metaheuristics and standard terminal sliding mode approaches.Numerical simulations are carried out to show the effectiveness and superiority of the proposed GWO-tuned FTSM controllers for the altitude and attitude dynamics’stabilization and tracking.Nonparametric statistical analyses revealed that the GWO algorithm is more competitive with high performance in terms of fastness,non-premature convergence,and research exploration/exploitation capabilities.展开更多
This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler form...This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler formalism,a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes.Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law,which are usually selected by repetitive and time-consuming trials-errors based procedures,a constrained optimization problem is formulated for the systematically tuning of these unknown variables.Under time-domain operating constraints,such an optimization-based tuning problem is effectively solved using the proposed SFLA metaheuristic with an empirical comparison to other evolutionary computation-and swarm intelligence-based algorithms such as the Crow Search Algorithm(CSA),Fractional Particle Swarm Optimization Memetic Algorithm(FPSOMA),Ant Bee Colony(ABC)and Harmony Search Algorithm(HSA).Numerical experiments are carried out for various sets of algorithms’parameters to achieve optimal gains of the sliding mode controllers for the altitude and attitude dynamics stabilization.Comparative studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature convergence.Demonstrative results verified that the proposed metaheuristicsbased approach is a promising alternative for the systematic tuning of the effective design parameters in the integral sliding mode control framework.展开更多
This paper proposes the design and a comparative study of two nonlinear systems modeling techniques. These two approaches are developed to address a class of nonlinear systems with time-varying parameter. The first is...This paper proposes the design and a comparative study of two nonlinear systems modeling techniques. These two approaches are developed to address a class of nonlinear systems with time-varying parameter. The first is a Radial Basis Function (RBF) neural networks and the second is a Multi Layer Perceptron (MLP). The MLP model consists of an input layer, an output layer and usually one or more hidden layers. However, training MLP network based on back propagation learning is computationally expensive. In this paper, an RBF network is called. The parameters of the RBF model are optimized by two methods: the Gradient Descent (GD) method and Genetic Algorithms (GA). However, the MLP model is optimized by the Gradient Descent method. The performance of both models are evaluated first by using a numerical simulation and second by handling a chemical process known as the Continuous Stirred Tank Reactor CSTR. It has been shown that in both validation operations the results were successful. The optimized RBF model by Genetic Algorithms gave the best results.展开更多
The purpose of this paper is looking for associations between environmental factors and morphological parameters in tambaqui （Piaractus brachypomus） individuals to differentiate this species in lentic environments ...The purpose of this paper is looking for associations between environmental factors and morphological parameters in tambaqui （Piaractus brachypomus） individuals to differentiate this species in lentic environments （lake） and lotic （river）. In this, regard studied 30 specimens, 15 from lentic environment （lake） and 15 from lotic （river）. Also, on right profile of these 25 morphometric variables were measured. On data matrix a PCA （principal components analysis） based on morphometric correlations matrix, which was defined in the new morphologic space of these specimens （3 principal components） which explain 73.23% of variability. Fish projection in first two principal components showed a morphological differentiation between two environments （lentic and lotic）, with variables as, horizontal eye diameter, length maxilla, suggesting greater response of these fish in lotic environment by their adaptation to light conditions, predators threat and food distribution. Finally, in lotic environment these fish have thinner caudal peduncle, indicating greater plasticity, namely stylized fish.展开更多
This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal mod...This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.展开更多
In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-o...In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.展开更多
The present paper aims at validating a Model Predictive Control(MPC),based on the Mixed Logical Dynamical(MLD)model,for Hybrid Dynamic Systems(HDSs)that explicitly involve continuous dynamics and discrete events.The p...The present paper aims at validating a Model Predictive Control(MPC),based on the Mixed Logical Dynamical(MLD)model,for Hybrid Dynamic Systems(HDSs)that explicitly involve continuous dynamics and discrete events.The proposed benchmark system is a three-tank process,which is a typical case study of HDSs.The MLD-MPC controller is applied to the level control of the considered tank system.The study is initially focused on the MLD approach that allows consideration of the interacting continuous dynamics with discrete events and includes the operating constraints.This feature of MLD modeling is very advantageous when an MPC controller synthesis for the HDSs is designed.Once the MLD model of the system is well-posed,then the MPC law synthesis can be developed based on the Mixed Integer Programming(MIP)optimization problem.For solving this MIP problem,a Branch and Bound(B&B)algorithm is proposed to determine the optimal control inputs.Then,a comparative study is carried out to illustrate the effectiveness of the proposed hybrid controller for the HDSs compared to the standard MPC approach.Performances results show that the MLD-MPC approach outperforms the standardMPCone that doesn’t consider the hybrid aspect of the system.The paper also shows a behavioral test of the MLDMPC controller against disturbances deemed as liquid leaks from the system.The results are very satisfactory and show that the tracking error is minimal less than 0.1%in nominal conditions and less than 0.6%in the presence of disturbances.Such results confirm the success of the MLD-MPC approach for the control of the HDSs.展开更多
Paths planning of Unmanned Aerial Vehicles(UAVs)in a dynamic environment is considered a challenging task in autonomous flight control design.In this work,an efficient method based on a Multi-Objective MultiVerse Opti...Paths planning of Unmanned Aerial Vehicles(UAVs)in a dynamic environment is considered a challenging task in autonomous flight control design.In this work,an efficient method based on a Multi-Objective MultiVerse Optimization(MOMVO)algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles.Such a path planning task is formulated as a multicriteria optimization problem under operational constraints.The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles.The vehicle moves to the next position from its current one such that the line joining minimizes the total path length and allows aligning its direction towards the goal.To choose the best compromise solution among all the non-dominated Pareto ones obtained for compromise objectives,the modified Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)is investigated.A set of homologous metaheuristics such as Multiobjective Salp Swarm Algorithm(MSSA),Multi-Objective Grey Wolf Optimizer(MOGWO),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-Dominated Genetic Algorithm II(NSGAII)is used as a basis for the performance comparison.Demonstrative results and statistical analyses show the superiority and effectiveness of the proposed MOMVO-based planning method.The obtained results are satisfactory and encouraging for future practical implementation of the path planning strategy.展开更多
Using the Lie algebraic method the vibrational frequencies of 97 resonances Raman lines (A1g + B1g + A2g + B2g) and 38 infrared bands (Eu) of octaethylporphyrinato-Ni (II) and its mesodeuterated and 15N-substituted de...Using the Lie algebraic method the vibrational frequencies of 97 resonances Raman lines (A1g + B1g + A2g + B2g) and 38 infrared bands (Eu) of octaethylporphyrinato-Ni (II) and its mesodeuterated and 15N-substituted derivates and Fullerenes C60 and Cv70 of 7 vibrational bands are calculated using U(2) algebraic Hamiltonian with four fitting algebraic parameters. The results obtained by the algebraic technique have been compared with experimental data;and they show great accuracy.展开更多
This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management succe...This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management success,being a new entrepreneurial management,with support of this new technology in the reduction of costs and increased value added.HMS is in the process of being developed in the so-called"Consortium of the Rich Countries for the 21st Century",which involves governments,companies and universities from the first world countries,developing technology and knowledge related to the Holonic Manufacturing System(HMS).This new concept,under development by the above consortium,will allow the countries that hold this advancement to overcome the challenges of the globalized market and gain even more international competitiveness.展开更多
With the new theoretical approach i.e. lie algebraic approach, we have calculated the infrared spectra of Phosphine in the range from 3000 cm-1 to 9500 cm-1 and Nitrogen Trifluoride in the range from 900 cm-1 to 4500 ...With the new theoretical approach i.e. lie algebraic approach, we have calculated the infrared spectra of Phosphine in the range from 3000 cm-1 to 9500 cm-1 and Nitrogen Trifluoride in the range from 900 cm-1 to 4500 cm-1. The model Hamiltonian, so constructed, seems to describe the P-H and N-F stretching modes accurately with only four numbers of parameters.展开更多
The controlling and synchronizing chaotic systems(CSs)are crucial aspects of engineering,with broad applications across various applied sciences,such as secure communications,nonlinear circuit design,biomedical engine...The controlling and synchronizing chaotic systems(CSs)are crucial aspects of engineering,with broad applications across various applied sciences,such as secure communications,nonlinear circuit design,biomedical engineering,and image processing.This paper deals with the complex problem of achieving finite-time projective synchronization for uncertain CSs with incommensurate non-integer orders using adaptive fuzzy sliding-mode control(AFSMC).Specifically,we focus on practical projective synchronization,introducing two novel control approaches that effectively mitigate the chattering phenomenon,a common issue in conventional sliding mode control.To achieve this,two innovative non-singular sliding surfaces with finite-time properties are formulated.This type of sliding surface enhances projective synchronization accuracy,response speed,and robustness.The adaptive fuzzy logic systems,known for their universal approximation capability,are employed to estimate continuous functional uncertainties.We rigorously analyzed the stability of both approaches using Lyapunov’s direct method.Extensive simulations confirm the effectiveness and benefits of our proposed methods.These methods significantly reduce or eliminate chattering and achieve practical projective synchronization in a finite time.This makes them well-suited for real-world applications in complex CSs.展开更多
This paper presents an innovative way to enhance the performance of photovoltaic(PV)arrays under uneven shadowing conditions.The study focuses on a triple-series–parallel ladder configuration to exploit the benefits ...This paper presents an innovative way to enhance the performance of photovoltaic(PV)arrays under uneven shadowing conditions.The study focuses on a triple-series–parallel ladder configuration to exploit the benefits of increased power generation while ad-dressing the challenges associated with uneven shadowing.The proposed methodology focuses on the implementation of improved sliding-mode control technique for efficient global maximum power point tracking.Sliding-mode control is known for its robustness in the presence of uncertainties and disturbances,making it suitable for dynamic and complex systems such as PV arrays.This work employs a comprehensive simulation framework to comment on the performance of the suggested improved sliding-mode control strategy in uneven shadowing scenarios.Comparative analysis has been done to show the better effectiveness of the suggested method than the traditional control strategies.The results demonstrate a remarkable enhancement in the tracking accuracy of the global maximum power point,leading to enhanced energy-harvesting capabilities under challenging environmental conditions.Furthermore,the proposed approach exhibits robustness and adaptability in mitigating the effect of shading on the PV array,thereby increasing overall system efficiency.This research contributes valuable insights into the development of advanced control strategies for PV arrays,particularly in the context of triple-series–parallel ladder configurations operating under uneven shadowing conditions.Under short narrow shading conditions,the improved sliding-mode control method tracks the maximum power better compared with perturb&observe at 20.68%,incremental-conductance at 68.78%,fuzzy incremental-conductance at 19.8%,and constant-velocity sliding-mode control at 1.25%.The improved sliding-mode control method has 60%less chattering than constant-velocity sliding-mode control under shading conditions.展开更多
This paper addresses the power quality improvement of a single-phase utility grid using a thirteen-level dualboost inverter(TLDBI)-shunt active filter(SAF).The TLDBI uses a single DC source of low voltage magnitude an...This paper addresses the power quality improvement of a single-phase utility grid using a thirteen-level dualboost inverter(TLDBI)-shunt active filter(SAF).The TLDBI uses a single DC source of low voltage magnitude and five switched capacitor arrangement to achieve self-balanced thirteen level output voltages.Moreover,the charging and voltage balancing of the capacitor is achieved by proper switching sequence control in a series,through which boosted inverter output voltage levels are obtained.Compared with the tradional H-bridge multilevel inverters(MLIs),all the elements in the proposed TLDBI are able to withstand a voltage stress which is equal to the input DC source.This feature ensures the performance of the proposed TLDBI in high-frequency applications.The power at the electrical grid is highly affected by a wide range of non-linear loads.The proposed SAF is used for measuring and controlling the current flow from source to load.The difference between the targeted and actual currents from the utility grid is measured by using the modified synchronous reference frame(SRF)theory.The estimated error current is used by the controllers to predict the optimum suitable switching angle and modulation index(MI)to the TLDBI-SAF.In this paper,the traditional proportional-integral(PI)controller,fuzzy logic controller(FLC)and proportional resonant controller(PRC)are compared and the results are presented to validate the performance of SAF.The stability and robustness of the proposed controller is evaluated using Bode,Root locus,and Nyquist plots.The modeling and analysis of the proposed system are done using MATLAB/Simulink environments.The simulation results are presented in the various MI of TLDBI and also subjected to non-linear load conditions.The results are also compared to the claim novelty of the proposed study.展开更多
文摘In this research paper,an improved strategy to enhance the performance of the DC-link voltage loop regulation in a Doubly Fed Induction Generator(DFIG)based wind energy system has been proposed.The proposed strategy used the robust Fractional-Order(FO)Proportional-Integral(PI)control technique.The FOPI control contains a non-integer order which is preferred over the integer-order control owing to its benefits.It offers extra flexibility in design and demonstrates superior outcomes such as high robustness and effectiveness.The optimal gains of the FOPI controller have been determined using a recent Manta Ray Foraging Optimization(MRFO)algorithm.During the optimization process,the FOPI controller’s parameters are assigned to be the decision variables whereas the objective function is the error racking that to be minimized.To prove the superiority of the MRFO algorithm,an empirical comparison study with the homologous particle swarm optimization and genetic algorithm is achieved.The obtained results proved the superiority of the introduced strategy in tracking and control performances against various conditions such as voltage dips and wind speed variation.
文摘The research on Unmanned Aerial Vehicles(UAV)has intensified considerably thanks to the recent growth in the fields of advanced automatic control,artificial intelligence,and miniaturization.In this paper,a Grey Wolf Optimization(GWO)algorithm is proposed and successfully applied to tune all effective parameters of Fast Terminal Sliding Mode(FTSM)controllers for a quadrotor UAV.A full control scheme is first established to deal with the coupled and underactuated dynamics of the drone.Controllers for altitude,attitude,and position dynamics become separately designed and tuned.To work around the repetitive and time-consuming trial-error-based procedures,all FTSM controllers’parameters for only altitude and attitude dynamics are systematically tuned thanks to the proposed GWO metaheuristic.Such a hard and complex tuning task is formulated as a nonlinear optimization problem under operational constraints.The performance and robustness of the GWO-based control strategy are compared to those based on homologous metaheuristics and standard terminal sliding mode approaches.Numerical simulations are carried out to show the effectiveness and superiority of the proposed GWO-tuned FTSM controllers for the altitude and attitude dynamics’stabilization and tracking.Nonparametric statistical analyses revealed that the GWO algorithm is more competitive with high performance in terms of fastness,non-premature convergence,and research exploration/exploitation capabilities.
文摘This work presents a memetic Shuffled Frog Leaping Algorithm(SFLA)based tuning approach of an Integral Sliding Mode Controller(ISMC)for a quadrotor type of Unmanned Aerial Vehicles(UAV).Based on the Newton–Euler formalism,a nonlinear dynamic model of the studied quadrotor is firstly established for control design purposes.Since the main parameters of the ISMC design are the gains of the sliding surfaces and signum functions of the switching control law,which are usually selected by repetitive and time-consuming trials-errors based procedures,a constrained optimization problem is formulated for the systematically tuning of these unknown variables.Under time-domain operating constraints,such an optimization-based tuning problem is effectively solved using the proposed SFLA metaheuristic with an empirical comparison to other evolutionary computation-and swarm intelligence-based algorithms such as the Crow Search Algorithm(CSA),Fractional Particle Swarm Optimization Memetic Algorithm(FPSOMA),Ant Bee Colony(ABC)and Harmony Search Algorithm(HSA).Numerical experiments are carried out for various sets of algorithms’parameters to achieve optimal gains of the sliding mode controllers for the altitude and attitude dynamics stabilization.Comparative studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature convergence.Demonstrative results verified that the proposed metaheuristicsbased approach is a promising alternative for the systematic tuning of the effective design parameters in the integral sliding mode control framework.
文摘This paper proposes the design and a comparative study of two nonlinear systems modeling techniques. These two approaches are developed to address a class of nonlinear systems with time-varying parameter. The first is a Radial Basis Function (RBF) neural networks and the second is a Multi Layer Perceptron (MLP). The MLP model consists of an input layer, an output layer and usually one or more hidden layers. However, training MLP network based on back propagation learning is computationally expensive. In this paper, an RBF network is called. The parameters of the RBF model are optimized by two methods: the Gradient Descent (GD) method and Genetic Algorithms (GA). However, the MLP model is optimized by the Gradient Descent method. The performance of both models are evaluated first by using a numerical simulation and second by handling a chemical process known as the Continuous Stirred Tank Reactor CSTR. It has been shown that in both validation operations the results were successful. The optimized RBF model by Genetic Algorithms gave the best results.
文摘The purpose of this paper is looking for associations between environmental factors and morphological parameters in tambaqui （Piaractus brachypomus） individuals to differentiate this species in lentic environments （lake） and lotic （river）. In this, regard studied 30 specimens, 15 from lentic environment （lake） and 15 from lotic （river）. Also, on right profile of these 25 morphometric variables were measured. On data matrix a PCA （principal components analysis） based on morphometric correlations matrix, which was defined in the new morphologic space of these specimens （3 principal components） which explain 73.23% of variability. Fish projection in first two principal components showed a morphological differentiation between two environments （lentic and lotic）, with variables as, horizontal eye diameter, length maxilla, suggesting greater response of these fish in lotic environment by their adaptation to light conditions, predators threat and food distribution. Finally, in lotic environment these fish have thinner caudal peduncle, indicating greater plasticity, namely stylized fish.
文摘This work concerns the study of problems relating to the adaptive internal model control of DC motor in both cases conventional and neural. The most important aspects of design building blocks of adaptive internal model control are the choice of architectures, learning algorithms, and examples of learning. The choice of parametric adaptation algorithm for updating elements of the conventional adaptive internal model control shows limitations. To overcome these limitations, we chose the architectures of neural networks deduced from the conventional models and the Levenberg-marquardt during the adjustment of system parameters of the adaptive neural internal model control. The results of this latest control showed compensation for disturbance, good trajectory tracking performance and system stability.
文摘In this paper, an adaptive neuro-control structure for complex dynamic system is proposed. A recurrent Neural Network is trained-off-line to learn the inverse dynamics of the system from the observation of the input-output data. The direct adaptive approach is performed after the training process is achieved. A lyapunov-Base training algorithm is proposed and used to adjust on-line the network weights so that the neural model output follows the desired one. The simulation results obtained verify the effectiveness of the proposed control method.
文摘The present paper aims at validating a Model Predictive Control(MPC),based on the Mixed Logical Dynamical(MLD)model,for Hybrid Dynamic Systems(HDSs)that explicitly involve continuous dynamics and discrete events.The proposed benchmark system is a three-tank process,which is a typical case study of HDSs.The MLD-MPC controller is applied to the level control of the considered tank system.The study is initially focused on the MLD approach that allows consideration of the interacting continuous dynamics with discrete events and includes the operating constraints.This feature of MLD modeling is very advantageous when an MPC controller synthesis for the HDSs is designed.Once the MLD model of the system is well-posed,then the MPC law synthesis can be developed based on the Mixed Integer Programming(MIP)optimization problem.For solving this MIP problem,a Branch and Bound(B&B)algorithm is proposed to determine the optimal control inputs.Then,a comparative study is carried out to illustrate the effectiveness of the proposed hybrid controller for the HDSs compared to the standard MPC approach.Performances results show that the MLD-MPC approach outperforms the standardMPCone that doesn’t consider the hybrid aspect of the system.The paper also shows a behavioral test of the MLDMPC controller against disturbances deemed as liquid leaks from the system.The results are very satisfactory and show that the tracking error is minimal less than 0.1%in nominal conditions and less than 0.6%in the presence of disturbances.Such results confirm the success of the MLD-MPC approach for the control of the HDSs.
文摘Paths planning of Unmanned Aerial Vehicles(UAVs)in a dynamic environment is considered a challenging task in autonomous flight control design.In this work,an efficient method based on a Multi-Objective MultiVerse Optimization(MOMVO)algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles.Such a path planning task is formulated as a multicriteria optimization problem under operational constraints.The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles.The vehicle moves to the next position from its current one such that the line joining minimizes the total path length and allows aligning its direction towards the goal.To choose the best compromise solution among all the non-dominated Pareto ones obtained for compromise objectives,the modified Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)is investigated.A set of homologous metaheuristics such as Multiobjective Salp Swarm Algorithm(MSSA),Multi-Objective Grey Wolf Optimizer(MOGWO),Multi-Objective Particle Swarm Optimization(MOPSO),and Non-Dominated Genetic Algorithm II(NSGAII)is used as a basis for the performance comparison.Demonstrative results and statistical analyses show the superiority and effectiveness of the proposed MOMVO-based planning method.The obtained results are satisfactory and encouraging for future practical implementation of the path planning strategy.
文摘Using the Lie algebraic method the vibrational frequencies of 97 resonances Raman lines (A1g + B1g + A2g + B2g) and 38 infrared bands (Eu) of octaethylporphyrinato-Ni (II) and its mesodeuterated and 15N-substituted derivates and Fullerenes C60 and Cv70 of 7 vibrational bands are calculated using U(2) algebraic Hamiltonian with four fitting algebraic parameters. The results obtained by the algebraic technique have been compared with experimental data;and they show great accuracy.
文摘This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management success,being a new entrepreneurial management,with support of this new technology in the reduction of costs and increased value added.HMS is in the process of being developed in the so-called"Consortium of the Rich Countries for the 21st Century",which involves governments,companies and universities from the first world countries,developing technology and knowledge related to the Holonic Manufacturing System(HMS).This new concept,under development by the above consortium,will allow the countries that hold this advancement to overcome the challenges of the globalized market and gain even more international competitiveness.
文摘With the new theoretical approach i.e. lie algebraic approach, we have calculated the infrared spectra of Phosphine in the range from 3000 cm-1 to 9500 cm-1 and Nitrogen Trifluoride in the range from 900 cm-1 to 4500 cm-1. The model Hamiltonian, so constructed, seems to describe the P-H and N-F stretching modes accurately with only four numbers of parameters.
基金supported by the General Directorate of Scientific Research and Technological Development(DGRSDT)of the Ministry of Higher Education and Scientific Research of Algeria,under Grant No.A01L08UN180120230001.
文摘The controlling and synchronizing chaotic systems(CSs)are crucial aspects of engineering,with broad applications across various applied sciences,such as secure communications,nonlinear circuit design,biomedical engineering,and image processing.This paper deals with the complex problem of achieving finite-time projective synchronization for uncertain CSs with incommensurate non-integer orders using adaptive fuzzy sliding-mode control(AFSMC).Specifically,we focus on practical projective synchronization,introducing two novel control approaches that effectively mitigate the chattering phenomenon,a common issue in conventional sliding mode control.To achieve this,two innovative non-singular sliding surfaces with finite-time properties are formulated.This type of sliding surface enhances projective synchronization accuracy,response speed,and robustness.The adaptive fuzzy logic systems,known for their universal approximation capability,are employed to estimate continuous functional uncertainties.We rigorously analyzed the stability of both approaches using Lyapunov’s direct method.Extensive simulations confirm the effectiveness and benefits of our proposed methods.These methods significantly reduce or eliminate chattering and achieve practical projective synchronization in a finite time.This makes them well-suited for real-world applications in complex CSs.
文摘This paper presents an innovative way to enhance the performance of photovoltaic(PV)arrays under uneven shadowing conditions.The study focuses on a triple-series–parallel ladder configuration to exploit the benefits of increased power generation while ad-dressing the challenges associated with uneven shadowing.The proposed methodology focuses on the implementation of improved sliding-mode control technique for efficient global maximum power point tracking.Sliding-mode control is known for its robustness in the presence of uncertainties and disturbances,making it suitable for dynamic and complex systems such as PV arrays.This work employs a comprehensive simulation framework to comment on the performance of the suggested improved sliding-mode control strategy in uneven shadowing scenarios.Comparative analysis has been done to show the better effectiveness of the suggested method than the traditional control strategies.The results demonstrate a remarkable enhancement in the tracking accuracy of the global maximum power point,leading to enhanced energy-harvesting capabilities under challenging environmental conditions.Furthermore,the proposed approach exhibits robustness and adaptability in mitigating the effect of shading on the PV array,thereby increasing overall system efficiency.This research contributes valuable insights into the development of advanced control strategies for PV arrays,particularly in the context of triple-series–parallel ladder configurations operating under uneven shadowing conditions.Under short narrow shading conditions,the improved sliding-mode control method tracks the maximum power better compared with perturb&observe at 20.68%,incremental-conductance at 68.78%,fuzzy incremental-conductance at 19.8%,and constant-velocity sliding-mode control at 1.25%.The improved sliding-mode control method has 60%less chattering than constant-velocity sliding-mode control under shading conditions.
文摘This paper addresses the power quality improvement of a single-phase utility grid using a thirteen-level dualboost inverter(TLDBI)-shunt active filter(SAF).The TLDBI uses a single DC source of low voltage magnitude and five switched capacitor arrangement to achieve self-balanced thirteen level output voltages.Moreover,the charging and voltage balancing of the capacitor is achieved by proper switching sequence control in a series,through which boosted inverter output voltage levels are obtained.Compared with the tradional H-bridge multilevel inverters(MLIs),all the elements in the proposed TLDBI are able to withstand a voltage stress which is equal to the input DC source.This feature ensures the performance of the proposed TLDBI in high-frequency applications.The power at the electrical grid is highly affected by a wide range of non-linear loads.The proposed SAF is used for measuring and controlling the current flow from source to load.The difference between the targeted and actual currents from the utility grid is measured by using the modified synchronous reference frame(SRF)theory.The estimated error current is used by the controllers to predict the optimum suitable switching angle and modulation index(MI)to the TLDBI-SAF.In this paper,the traditional proportional-integral(PI)controller,fuzzy logic controller(FLC)and proportional resonant controller(PRC)are compared and the results are presented to validate the performance of SAF.The stability and robustness of the proposed controller is evaluated using Bode,Root locus,and Nyquist plots.The modeling and analysis of the proposed system are done using MATLAB/Simulink environments.The simulation results are presented in the various MI of TLDBI and also subjected to non-linear load conditions.The results are also compared to the claim novelty of the proposed study.
