Journal ArticleDOI
Position control of nonlinear hydraulic system using an improved PSO based PID controller
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TLDR
In this article, an improved particle swarm optimization (PSO) algorithm is presented to search for the optimal proportional-integral-derivative (PID) controller gains for the nonlinear hydraulic system.About:
This article is published in Mechanical Systems and Signal Processing.The article was published on 2017-01-15. It has received 115 citations till now. The article focuses on the topics: PID controller & Particle swarm optimization.read more
Citations
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Journal ArticleDOI
Robotic excavator trajectory control using an improved GA based PID controller
TL;DR: It was demonstrated from the experimental work that the proposed IGA based PID controller improves the trajectory accuracy of the horizontal line and slope line trajectories by 23.98% and 23.64%, respectively in comparison to the SGA tuned PID controller.
Journal ArticleDOI
Kalman filter for mobile-robot attitude estimation: Novel optimized and adaptive solutions
TL;DR: Two novel approaches to estimate accurately mobile robot attitudes based on the fusion of low-cost accelerometers and gyroscopes are proposed and a novel adaptive Kalman filter structure is introduced that modifies the noise covariance values according to the system dynamics.
Journal ArticleDOI
Trajectory control of electro-hydraulic position servo system using improved PSO-PID controller
TL;DR: Simulation results illustrate that high accuracy and fast convergence can be obtained based on the improved PSO algorithm PID controller (IPSO-PID), and demonstrated that the IPSO-BPSO method can achieve the highest tracking accuracy.
Journal ArticleDOI
Effect of pre-deformation on creep age forming of 2219 aluminum alloy: Experimental and constitutive modelling
TL;DR: In this article, the effects of pre-deformation on shape formation and mechanical properties of a pre-stretched AA2219 component were investigated, and a set of physically-based creep ageing constitutive model was proposed to predict shape and properties in large-scale panel component.
Journal ArticleDOI
Optimized PID Controller Based on Beetle Antennae Search Algorithm for Electro-Hydraulic Position Servo Control System.
Yuqi Fan,Junpeng Shao,Guitao Sun +2 more
TL;DR: Comparing the effectiveness of different algorithms, simulation and experimental results revealed that the BAS-PID controller can greatly enhance the performance of the electro-hydraulic position servo control system and inhibit external disturbances when different interference signals are used to test the system’s robustness.
References
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Proceedings ArticleDOI
Particle swarm optimization
TL;DR: A concept for the optimization of nonlinear functions using particle swarm methodology is introduced, and the evolution of several paradigms is outlined, and an implementation of one of the paradigm is discussed.
Proceedings ArticleDOI
A modified particle swarm optimizer
Yuhui Shi,Russell C. Eberhart +1 more
TL;DR: A new parameter, called inertia weight, is introduced into the original particle swarm optimizer, which resembles a school of flying birds since it adjusts its flying according to its own flying experience and its companions' flying experience.
Proceedings ArticleDOI
The swarm and the queen: towards a deterministic and adaptive particle swarm optimization
TL;DR: A very simple particle swarm optimization iterative algorithm is presented, with just one equation and one social/confidence parameter, and the results are good enough so that it is certainly worthwhile trying the method on more complex problems.
Proceedings ArticleDOI
Tracking and optimizing dynamic systems with particle swarms
Russell C. Eberhart,Yuhui Shi +1 more
TL;DR: Three kinds of dynamic systems are defined for the purposes of this paper and one of them is chosen for preliminary analysis using the particle swarm on the parabolic benchmark function.
Related Papers (5)
Tuning of PID Controller Parameters Based on Improved Particle Swarm Optimization Algorithm
Optimization and Simulation of PID Parameters Based on Improved Particle Swarm Algorithms
Hao Wan-jun,Qiang Wen-yi +1 more