Sliding-mode PID Control of UAV Based on Particle Swarm Parameter Tuning

Background: The PWM Boost converter is a strongly nonlinear discrete system, especially when the input voltage or load varies widely, therefore, tuning the control parameters of which is a challenge work. Objective: In order to overcome the issues, particle swarm optimization (PSO) is employed for tuning the parameters of a sliding mode controller of a boost converter. Methods: Based on the analysis of the Boost converter model and its non-linear characteristics, a mathematic model of a boost converter with a sliding mode controller is built firstly. Then, the parameters of the Boost controller are adjusted based on the integrated time and absolute error (ITAE), integral square error (ISE) and integrated absolute error (IAE) indexes by PSO. Results: Simulation verification was performed, and the results show that the controllers tuned by the three indexes all have excellent robust stability. Conclusion: The controllers tuned by ITAE and ISE indexes have excellent steady-state performance, but the overshoot is large during the startup. The controller tuned by IAE index has better startup performance and slightly worse steady-state performance.

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Design of Sliding Mode Controller with Particle Swarm Optimization using Optimised PID Sliding

2020 9th International Conference System Modeling and Advancement in Research Trends (SMART) ◽

10.1109/smart50582.2020.9337133 ◽

2020 ◽

Author(s):

Shadvala K. Sebastian

Keyword(s):

Particle Swarm Optimization ◽

Sliding Mode ◽

Particle Swarm ◽

Sliding Mode Controller ◽

Swarm Optimization

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Research on Adaptive PID Control for Load Simulator with Varying Load

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.568-570.1031 ◽

2014 ◽

Vol 568-570 ◽

pp. 1031-1035

Author(s):

Ju Tian ◽

Yao Chen

Keyword(s):

Pid Control ◽

Simple Structure ◽

Control Method ◽

Parameter Tuning ◽

Hardware In The Loop ◽

Tuning Method ◽

Hydraulic Load ◽

Variation Characteristics ◽

Load Simulator ◽

Adaptive Pid Control

The electro-hydraulic load simulator is an important equipment for aircraft hardware-in-the-loop simulation. An adaptive PID control method for compensating extraneous torque with simple structure and easy to implement is proposed according to the variation characteristics of load gradient in the load simulator. The control parameter tuning method is also given.

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Particle Swarm optimization Based Fractional Order Sliding Mode Controller For Magnetic Levitation Systems

2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA) ◽

10.1109/iccca49541.2020.9250823 ◽

2020 ◽

Author(s):

Jesvin Jose ◽

S.J. Mija

Keyword(s):

Particle Swarm Optimization ◽

Fractional Order ◽

Magnetic Levitation ◽

Sliding Mode ◽

Particle Swarm ◽

Sliding Mode Controller ◽

Swarm Optimization

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A combined static output feedback-PID control for TITO process based particle swarm optimization: simulation and practical implementation for the poultry house system

International Journal of Dynamics and Control ◽

10.1007/s40435-021-00882-5 ◽

2022 ◽

Author(s):

Ilyas Lahlouh ◽

Fathallah Rerhrhaye ◽

Ahmed Elakkary ◽

Nacer Sefiani ◽

Abdelmajid Bybi

Keyword(s):

Particle Swarm Optimization ◽

Pid Control ◽

Output Feedback ◽

Particle Swarm ◽

Practical Implementation ◽

Static Output Feedback ◽

Swarm Optimization ◽

Poultry House ◽

Optimization Simulation ◽

Static Output

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FPGA implementation of adaptive sliding mode control and genetically optimized PID control for fractional-order induction motor system with uncertain load

Advances in Difference Equations ◽

10.1186/s13662-017-1341-9 ◽

2017 ◽

Vol 2017 (1) ◽

Cited By ~ 7

Author(s):

Karthikeyan Rajagopal ◽

Guessas Laarem ◽

Anitha Karthikeyan ◽

Ashokkumar Srinivasan

Keyword(s):

Sliding Mode Control ◽

Induction Motor ◽

Fractional Order ◽

Pid Control ◽

Motor System ◽

Sliding Mode ◽

Fpga Implementation ◽

Adaptive Sliding Mode Control ◽

Adaptive Sliding Mode ◽

Mode Control

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Position Control of Ultrasonic Motor Using IMC-PID Combined with Tribes Type NN Algorithm

Advanced Engineering Forum ◽

10.4028/www.scientific.net/aef.2-3.12 ◽

2011 ◽

Vol 2-3 ◽

pp. 12-17

Author(s):

Sheng Lin Mu ◽

Kanya Tanaka

Keyword(s):

Neural Network ◽

Particle Swarm Optimization ◽

Pid Control ◽

Position Control ◽

Back Propagation ◽

Particle Swarm ◽

Pso Algorithm ◽

Ultrasonic Motor ◽

Swarm Optimization

In this paper, we propose a novel scheme of IMC-PID control combined with a tribes type neural network (NN) for the position control of ultrasonic motor (USM). In this method, the NN controller is employed for tuning the parameter in IMC-PID control. The weights of NN are designed to be updated by the tribes-particle swarm optimization (PSO) algorithm. This method makes it possible to compensate for the characteristic changes and nonlinearity of USM. The parameter-free tribes-PSO requires no information about the USM beforehand; hence its application overcomes the problem of Jacobian estimation in the conventional back propagation (BP) method of NN. The effectiveness of the proposed method is confirmed by experiments.

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