Modified shuffled frog leaping algorithm for optimization of UAV flight controller

2011 ◽  
Vol 4 (1) ◽  
pp. 25-39 ◽  
Author(s):  
Huangzhong Pu ◽  
Ziyang Zhen ◽  
Daobo Wang
Keyword(s):  
Particle Swarm Optimization ◽  
Control System ◽  
Flight Control ◽  
Attitude Control ◽  
Optimization Method ◽  
Flight Control System ◽  
Shuffled Frog Leaping Algorithm ◽  
Swarm Optimization ◽  
Content Type ◽  
Shuffled Frog Leaping

PurposeAttitude control of unmanned aerial vehicle (UAV) is the purposeful manipulation of controllable external forces to establish a desired attitude, which is inner‐loop of the autonomous flight control system. In the practical applications, classical control methods such as proportional‐integral‐derivative control are usually selected because of simple and high reliability. However, it is usually difficult to select or optimize the control parameters. The purpose of this paper is to investigate an intelligent algorithm based classical controller of UAV.Design/methodology/approachAmong the many intelligent algorithms, shuffled frog leaping algorithm (SFLA) combines the benefits of the genetic‐based memetic algorithm as well as social behavior based particle swarm optimization. SFLA is a population based meta‐heuristic intelligent optimization method inspired by natural memetics. In order to improve the performance of SFLA, a different dividing method of the memeplexes is presented to make their performance balance; moreover, an evolution mechanism of the best frog is introduced to make the algorithm jump out the local optimum. The modified SFLA is applied to the tuning of the proportional coefficients of pitching and rolling channels of UAV flight control system.FindingsSimulation of a UAV control system in which the nonlinear model is obtained by the wind tunnel experiment show the rapid dynamic response and high control precision by using the modified SFLA optimized attitude controller, which is better than that of the original SFLA and particle swarm optimization method.Originality/valueA modification scheme is presented to improve the global searching capability of SFLA. The modified SFLA based intelligent determination method of the UAV flight controller parameters is proposed, in order to improve the attitude control performance of UAV.

scholarly journals Modified shuffled frog leaping algorithm optimized control for air-breathing hypersonic flight vehicle

2016 ◽  
Vol 13 (6) ◽  
pp. 172988141667813 ◽  
Author(s):  
Bingbing Liang ◽  
Ziyang Zhen ◽  
Ju Jiang
Keyword(s):  
Control System ◽  
Flight Control ◽  
Control Method ◽  
Hypersonic Vehicle ◽  
Pid Controllers ◽  
Flight Control System ◽  
Shuffled Frog Leaping Algorithm ◽  
Air Breathing ◽  
Nature Inspired Algorithm ◽  
Shuffled Frog Leaping

This article addresses the flight control problem of air-breathing hypersonic vehicles and proposes a novel intelligent algorithm optimized control method. To achieve the climbing, cruising and descending flight control of the air-breathing hypersonic vehicle, an engineering-oriented flight control system based on a Proportional Integral Derivative (PID) method is designed for the hypersonic vehicle, which including the height loop, the pitch angle loop and the velocity loop. Moreover, as a variant of nature-inspired algorithm, modified shuffled frog leaping algorithm is presented to optimize the flight control parameters and is characterized by better exploration and exploitation than the standard shuffled frog leaping algorithm. A nonlinear model of air-breathing hypersonic vehicle is used to verify the dynamic characteristics achieved by the intelligent flight control system. Simulation results demonstrate that the proposed swarm intelligence optimized PID controllers are effective in achieving better flight trajectory and velocity control performance than the traditional controllers.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

A novel sensor array and classifier optimization method of electronic nose based on enhanced quantum-behaved particle swarm optimization

Sensor Review ◽  
2014 ◽  
Vol 34 (3) ◽  
pp. 304-311 ◽  
Author(s):  
Pengfei Jia ◽  
Fengchun Tian ◽  
Shu Fan ◽  
Qinghua He ◽  
Jingwei Feng ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Wound Infection ◽  
Electronic Nose ◽  
Classification Accuracy ◽  
Sensor Array ◽  
Particle Swarm ◽  
Optimization Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Content Type

Purpose – The purpose of the paper is to propose a new optimization algorithm to realize a synchronous optimization of sensor array and classifier, to improve the performance of E-nose in the detection of wound infection. When an electronic nose (E-nose) is used to detect the wound infection, sensor array’s optimization and parameters’ setting of classifier have a strong impact on the classification accuracy. Design/methodology/approach – An enhanced quantum-behaved particle swarm optimization based on genetic algorithm, genetic quantum-behaved particle swarm optimization (G-QPSO), is proposed to realize a synchronous optimization of sensor array and classifier. The importance-factor (I-F) method is used to weight the sensors of E-nose by its degree of importance in classification. Both radical basis function network and support vector machine are used for classification. Findings – The classification accuracy of E-nose is the highest when the weighting coefficients of the I-F method and classifier’s parameters are optimized by G-QPSO. All results make it clear that the proposed method is an ideal optimization method of E-nose in the detection of wound infection. Research limitations/implications – To make the proposed optimization method more effective, the key point of further research is to enhance the classifier of E-nose. Practical implications – In this paper, E-nose is used to distinguish the class of wound infection; meanwhile, G-QPSO is used to realize a synchronous optimization of sensor array and classifier of E-nose. These are all important for E-nose to realize its clinical application in wound monitoring. Originality/value – The innovative concept improves the performance of E-nose in wound monitoring and paves the way for the clinical detection of E-nose.

Effects of the actively morphing root chord and taper on helicopter energy

2019 ◽  
Vol 92 (2) ◽  
pp. 264-270
Author(s):  
Firat Sal
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Flight Control ◽  
Design Methodology ◽  
Chord Length ◽  
Flight Control System ◽  
Content Type ◽  
Helicopter Blade ◽  
Blade Root ◽  
Practical Implications

Purpose The purpose of this paper presents the effects of actively morphing root chord and taper on the energy of the flight control system (i.e. FCS). Design/methodology/approach Via regarding previously mentioned purposes, sophisticated and realistic helicopter models are benefitted to examine the energy of the FCS. Findings Helicopters having actively morphing blade root chord length and blade taper consume less control energy than the ones having one of or any of passively morphing blade root chord length and blade taper. Practical implications Actively morphing blade root chord length and blade taper can be used for cheaper helicopter operations. Originality/value The main originality of this paper is applying active morphing strategy on helicopter blade root chord and blade taper. In this paper, it is also found that using active morphing strategy on helicopter blade root chord and blade taper reasons less energy consumption than using either passively morphing blade root chord length plus blade taper or not any. This causes also less fuel consumption and green environment.

Sensitivity of automatic control of emergency manoeuvre to parametric uncertainty of the airplane model

2019 ◽  
Vol 91 (3) ◽  
pp. 407-419
Author(s):  
Jerzy Graffstein ◽  
Piotr Maslowski
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Flight Control ◽  
Parametric Uncertainty ◽  
Second Phase ◽  
Flight Control System ◽  
Content Type ◽  
Control Quality ◽  
Wide Range ◽  
The Impact

Purpose The main purpose of this work was elaboration and verification of a method of assessing the sensitivity of automatic control laws to parametric uncertainty of an airplane’s mathematical model. The linear quadratic regulator (LQR) methodology was used as an example design procedure for the automatic control of an emergency manoeuvre. Such a manoeuvre is assumed to be pre-designed for the selected airplane. Design/methodology/approach The presented method of investigating the control systems’ sensitivity comprises two main phases. The first one consists in computation of the largest variations of gain factors, defined as differences between their nominal values (defined for the assumed model) and the values obtained for the assumed range of parametric uncertainty. The second phase focuses on investigating the impact of the variations of these factors on the behaviour of automatic control in the manoeuvre considered. Findings The results obtained allow for a robustness assessment of automatic control based on an LQR design. Similar procedures can be used to assess in automatic control arrived at through varying design methods (including methods other than LQR) used to control various manoeuvres in a wide range of flight conditions. Practical implications It is expected that the presented methodology will contribute to improvement of automatic flight control quality. Moreover, such methods should reduce the costs of the mathematical nonlinear model of an airplane through determining the necessary accuracy of the model identification process, needed for assuring the assumed control quality. Originality/value The presented method allows for the investigation of the impact of the parametric uncertainty of the airplane’s model on the variations of the gain-factors of an automatic flight control system. This also allows for the observation of the effects of such variations on the course of the selected manoeuvre or phase of flight. This might be a useful tool for the design of crucial elements of an automatic flight control system.

A dynamic particle swarm optimization method applied to global optimizations of engineering inverse problem

2018 ◽  
Vol 37 (1) ◽  
pp. 98-117 ◽  
Author(s):  
Shafiullah Khan ◽  
Shiyou Yang ◽  
Obaid Ur Rehman
Keyword(s):  
Inverse Problem ◽  
Particle Swarm Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Content Type ◽  
Novel Strategy ◽  
Modified Pso

Purpose The aim of this paper is to explore the potential of particle swarm optimization (PSO) algorithm to solve an electromagnetic inverse problem. Design/methodology/approach A modified PSO algorithm is designed. Findings The modified PSO algorithm is a more stable, robust and efficient global optimizer for solving the well-known benchmark optimization problems. The new mutation approach preserves the diversity of the population, whereas the proposed dynamic and adaptive parameters maintain a good balance between the exploration and exploitation searches. The numerically experimental results of two case studies demonstrate the merits of the proposed algorithm. Originality/value Some improvements, such as the design of a new global mutation mechanism and introducing a novel strategy for learning and control parameters, are proposed.

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