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Control Strategy for a Quadrotor Based on a Memetic shuffled frog leaping algorithm

Computers, Materials & Continua 2021年第6期67卷 4081-4100页

作者： Nour Ben Ammar Hegazy Rezk Soufiene Bouallègue Research Laboratory in Automatic Control(LARA) National Engineering School of Tunis(ENIT)University of Tunis EL MANARLe BelvédèreTunis1002Tunisia College of Engineering at Wadi Addawaser Prince Sattam Bin Abdulaziz UniversityAl-Kharj11911Saudi Arabia Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61517Egypt High Institute of Industrial Systems of Gabès(ISSIG) University of GabèsGabès6011Tunisia

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 *** 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 *** 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 *** studies revealed that the SFLA is a competitive and easily implemented algorithm with high performance in terms of robustness and non-premature *** 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.

关键词： Quadrotor modeling integral sliding mode control gains tuning advanced metaheuristics memetic algorithms shuffled frog leaping algorithm

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Improved shuffled frog leaping algorithm Optimizing Integral Separated PID Control for Unmanned Hypersonic Vehicle

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Transactions of Nanjing University of Aeronautics and Astronautics 2015年第1期32卷 110-114页

作者：梁冰冰江驹甄子洋马坤 College of Automation Engineering Nanjing University of Aeronautics and Astronautics

To solve the flight control problem for unmanned hypersonic vehicles,a novel intelligent optimized control method is proposed.A flight control system based on integral separated proportional-integral-derivative(PID)control is designed for hypersonic vehicle,and an improved shuffled frog leaping algorithm is presented to optimize the control parameters.A nonlinear model of hypersonic vehicle is established to examine the dynamic characteristics achieved by the flight control *** results demonstrate that the proposed optimized controller can effectively achieve better flight control performance than the traditional controller.

关键词： hypersonic vehicles flight control shuffled frog leaping algorithm unmanned aerial vehicles(UAVs)

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Stochastic Transmission Expansion Planning Incorporating Reliability Solved Using SFLA Meta-heuristic Optimization Technique

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CSEE Journal of Power and Energy Systems 2016年第2期2卷 79-86页

作者： Saedeh Alaee Rahmat-Allah Hooshmand Reza Hemmati Department of Electrical Engineering University of IsfahanIsfahanIran Department of Electrical Engineering Kermanshah University of TechnologyKermanshahIran

This paper addresses stochastic transmission expansion planning(TEP)under uncertain load conditions when reliability is taken into *** main objective of the proposed TEP is to minimize the total planning cost by denoting the place,number,and type of new transmission lines subject to safe operation *** this paper,the objective function consists of two terms,namely,investment cost(IC)of new lines and reliability *** reliability cost is incorporated as the loss of load cost(LOLC).Network uncertainties in the form of loads are molded as Gaussian probability distribution function(PDF).Monte-Carlo simulation is applied to tackle the *** proposed stochastic TEP is expressed as constrained optimization planning and solved using shuffled frog leaping algorithm(SFLA)SFLA is compared to other optimization techniques such as particle swarm optimization(PSO)and genetic algorithms(GA).Finally,stochastic planning(planning including uncertainty)and deterministic planning(planning excluding uncertainty)are compared to demonstrate impacts of uncertainty on the *** results in different cases and scenarios verify the effectiveness and viability of the proposed stochastic TEP,including uncertainty and reliability.

关键词： Reliability shuffled frog leaping algorithm stochastic planning transmission expansion planning uncertainty

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Annoyance-type speech emotion detection in working environment

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Journal of Southeast University(English Edition) 2013年第4期29卷 366-371页

作者：王青云赵力梁瑞宇张潇丹东南大学信息科学与工程学院南京210096 南京工程学院通信工程学院南京211167

In order to recognize people＇s annoyance emotions in the working environment and evaluate emotional well- being, emotional speech in a work environment is induced to obtain adequate samples of emotional speech, and a Mandarin database with two thousands samples is built. In searching for annoyance-type emotion features, the prosodic feature and the voice quality feature parameters of the emotional statements are extracted first. Then an improved back propagation （BP） neural network based on the shuffled frog leaping algorithm （SFLA） is proposed to recognize the emotion. The recognition capability of the BP, radical basis function （RBF） and the SFLA neural networks are compared experimentally. The results show that the recognition ratio of the SFLA neural network is 4. 7% better than that of the BP neural network and 4. 3% better than that of the RBF neural network. The experimental results demonstrate that the random initial data trained by the SFLA can optimize the connection weights and thresholds of the neural network, speed up the convergence and improve the recognition rate.

关键词： speech emotion detection annoyance type sentence length shuffled frog leaping algorithm

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