Period Doubling Bifurcation Point Detection Strategy with Nested Layer Particle Swarm Optimization

2017 ◽  
Vol 27 (07) ◽  
pp. 1750101 ◽  
Author(s):  
Haruna Matsushita ◽  
Yusho Tomimura ◽  
Hiroaki Kurokawa ◽  
Takuji Kousaka
Keyword(s):  
Particle Swarm Optimization ◽  
Bifurcation Point ◽  
Particle Swarm ◽  
Period Doubling ◽  
Period Doubling Bifurcation ◽  
Swarm Optimization ◽  
Detection Strategy ◽  
The Stability ◽  
Point Detection ◽  
Discrete Time Dynamical Systems

This paper proposes a bifurcation point detection strategy based on nested layer particle swarm optimization (NLPSO). The NLPSO is performed by two particle swarm optimization (PSO) algorithms with a nesting structure. The proposed method is tested in detection experiments of period doubling bifurcation points in discrete-time dynamical systems. The proposed method directly detects the parameters of period doubling bifurcation regardless of the stability of the periodic point, but require no careful initialization, exact calculation or Lyapunov exponents. Moreover, the proposed method is an effective detection technique in terms of accuracy, robustness usability, and convergence speed.

scholarly journals DAMAGE DETECTION FOR UHPFRC COMMUNICATION TOWER BASED ON FREQUENCY DATA AND PARTICLE SWARM OPTIMIZATION

2019 ◽  
Vol 25 (6) ◽  
pp. 495-517
Author(s):  
Sarah Jabbar ◽  
Farzad Hejazi ◽  
Ammar N. Hanoon ◽  
Rizal S. M. Rashid
Keyword(s):  
Particle Swarm Optimization ◽  
High Performance ◽  
Particle Swarm ◽  
Correlation Factor ◽  
Fiber Reinforced Concrete ◽  
Swarm Optimization ◽  
Computational Procedures ◽  
The Stability ◽  
Reliability Performance ◽  
Communication Towers

Advances in the telecommunication and broadcasting sectors have increased the need for networking equipment of communication towers. Slender structures, such as towers, are sensitive to dynamic loads, such as vibration forces. Therefore, the stability and reliability performance of towers can be maintained effectively through the prompt detection, localization, and quantification of structural damages by obtaining the dynamic frequency response of towers. However, frequency analysis for damaged structures requires long computational procedures and is difficult to perform because of the damages in real structures, particularly in towers. Therefore, this study proposed a correlation factor that can identify the relationship between frequenciesunderhealthy and damaged conditions of ultra high performance fiber-reinforced concrete (UHPFRC) communication towers using particle swarm optimization. The finite element method was implemented to simulate three UHPFRC communication towers, and an experimental test was conducted to validate and verify the developed correlation factor

scholarly journals A Novel Simple Particle Swarm Optimization Algorithm for Global Optimization

Mathematics ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 287 ◽  
Author(s):  
Xin Zhang ◽  
Dexuan Zou ◽  
Xin Shen
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Search Time ◽  
Success Rates ◽  
Swarm Optimization ◽  
Efficiency Of Algorithms ◽  
Fair Comparison ◽  
Random Weight ◽  
The Stability ◽  
Searching Ability

In order to overcome the several shortcomings of Particle Swarm Optimization (PSO) e.g., premature convergence, low accuracy and poor global searching ability, a novel Simple Particle Swarm Optimization based on Random weight and Confidence term (SPSORC) is proposed in this paper. The original two improvements of the algorithm are called Simple Particle Swarm Optimization (SPSO) and Simple Particle Swarm Optimization with Confidence term (SPSOC), respectively. The former has the characteristics of more simple structure and faster convergence speed, and the latter increases particle diversity. SPSORC takes into account the advantages of both and enhances exploitation capability of algorithm. Twenty-two benchmark functions and four state-of-the-art improvement strategies are introduced so as to facilitate more fair comparison. In addition, a t-test is used to analyze the differences in large amounts of data. The stability and the search efficiency of algorithms are evaluated by comparing the success rates and the average iteration times obtained from 50-dimensional benchmark functions. The results show that the SPSO and its improved algorithms perform well comparing with several kinds of improved PSO algorithms according to both search time and computing accuracy. SPSORC, in particular, is more competent for the optimization of complex problems. In all, it has more desirable convergence, stronger stability and higher accuracy.

scholarly journals Transient Stability Assessment by Coordinated Control of SVC and TCSC with Particle Swarm Optimization

2019 ◽  
Vol 9 (1) ◽  
pp. 2506-2510
Keyword(s):  
Particle Swarm Optimization ◽  
Transient Stability ◽  
Control Strategies ◽  
Particle Swarm ◽  
Coordinated Control ◽  
Pso Algorithm ◽  
Small Time ◽  
Local Power ◽  
Swarm Optimization ◽  
The Stability

This paper aims on improving the stability of a 9 bus power system under fault condition using coordination of FACTS device. Flexible A.C. transmission system (FACTS) can be regulated reliable with faster output and can improve local power grid status with control with appropriate control strategies in very small time period. Based on that, a particle swarm optimization (PSO) algorithm was executed, to design the coordinated parameter of static VAR compensator (SVC) and Thyristor Controlled Series Capacitor (TCSC). Simulation is performed on WSCC 9-bus system in MATLAB software. When 3 phase fault is applied near to generator, frequency and rotor angle changes accordingly. With coordinated control of FACTS devices with PSO has implemented both, near to its normal condition. PSO performed in this paper was structured on identifying the values of L and C of SVC and TCSC, for superior coordination.

scholarly journals Improve Linear Quadratic Regulator by Particle Swarm Optimization Algorithms for Two Wheeled Self Balancing Mobile robot

2017 ◽  
Vol 13 (2) ◽  
pp. 173-179
Author(s):  
Ekhlas Karam ◽  
Noor Mjeed
Keyword(s):  
Particle Swarm Optimization ◽  
Numerical Method ◽  
Control Method ◽  
Particle Swarm ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Swarm Optimization ◽  
Balancing Robot ◽  
The Stability ◽  
Multivariable Feedback

The aim of this paper is to suggest a methodical smooth control method for improving the stability of two wheeled self-balancing robot under effect disturbance. To promote the stability of the robot, the design of linear quadratic regulator using particle swarm optimization (PSO) method and adaptive particle swarm optimization (APSO). The computation of optimal multivariable feedback control is traditionally by LQR approach by Riccati equation. Regrettably, the method as yet has a trial and error approach when selecting parameters, particularly tuning the Q and R elements of the weight matrices. Therefore, an intelligent numerical method to solve this problem is suggested by depending PSO and APSO algorithm. To appraise the effectiveness of the suggested method, The Simulation result displays that the numerical method makes the system stable and minimizes processing time.

scholarly journals Pareto Optimal PID Tuning for Px4-Based Unmanned Aerial Vehicles by Using a Multi-Objective Particle Swarm Optimization Algorithm

Aerospace ◽  
2020 ◽  
Vol 7 (6) ◽  
pp. 71
Author(s):  
Victor Gomez ◽  
Nicolas Gomez ◽  
Jorge Rodas ◽  
Enrique Paiva ◽  
Maarouf Saad ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Unmanned Aerial Vehicles ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Pid Tuning ◽  
Aerial Vehicles ◽  
The Stability ◽  
Selection Of

Unmanned aerial vehicles (UAVs) are affordable these days. For that reason, there are currently examples of the use of UAVs in recreational, professional and research applications. Most of the commercial UAVs use Px4 for their operating system. Even though Px4 allows one to change the flight controller structure, the proportional-integral-derivative (PID) format is still by far the most popular choice. A selection of the PID controller parameters is required before the UAV can be used. Although there are guidelines for the design of PID parameters, they do not guarantee the stability of the UAV, which in many cases, leads to collisions involving the UAV during the calibration process. In this paper, an offline tuning procedure based on the multi-objective particle swarm optimization (MOPSO) algorithm for the attitude and altitude control of a Px4-based UAV is proposed. A Pareto dominance concept is used for the MOPSO to find values for the PID comparing parameters of step responses (overshoot, rise time and root-mean-square). Experimental results are provided to validate the proposed tuning procedure by using a quadrotor as a case study.

scholarly journals Impedance Controller Tuned by Particle Swarm Optimization for Robotic Arms

10.5772/45692 ◽  
2011 ◽  
Vol 8 (5) ◽  
pp. 57 ◽  
Author(s):  
Haifa Mehdi ◽  
Olfa Boubaker
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Fine Tuning ◽  
Fast Method ◽  
Constrained Motion ◽  
Circular Trajectory ◽  
Swarm Optimization ◽  
Robotic Arms ◽  
The Stability

This paper presents an efficient and fast method for fine tuning the controller parameters of robot manipulators in constrained motion. The stability of the robotic system is proved using a Lyapunov-based impedance approach whereas the optimal design of the controller parameters are tuned, in offline, by a Particle Swarm Optimization (PSO) algorithm. For designing the PSO method, different index performances are considered in both joint and Cartesian spaces. A 3DOF manipulator constrained to a circular trajectory is finally used to validate the performances of the proposed approach. The simulation results show the stability and the performances of the proposed approach.

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