scholarly journals PID Controller Tuning Optimization with Genetic Algorithms for a Quadcopter

2018 ◽  
Vol 5 (1.) ◽  
Author(s):  
Komal Khuwaja ◽  
Noor-u-Zaman Lighari ◽  
Ioan Constantin Tarca ◽  
Radu Catalin Tarca
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Controller Design ◽  
Sliding Mode ◽  
Gain Control ◽  
Nonlinear Gain ◽  
Pid Controller Tuning ◽  
Pid Controller Design ◽  
The Stability ◽  
Stability And Accuracy

This paper is focused on the dynamic of mathematical modeling, stability, nonlinear gain control by using Genetic algorithm, utilizing MATLAB tool of a quadcopter. Previously many researchers have been work on several linear controllers such as LQ method; sliding mode and classical PID are used to stabilize the Linear Model. Quadcopter has a nonlinear dynamics and unstable system. In order to maintain their stability, we use nonlinear gain controllers; classical PID controller provides linear gain controller rather than nonlinear gain controller; here we are using modified PID control to improve stability and accuracy. The stability is the state of being resistant to any change. The task is to maintain the quadcopter stability by improving the performance of a PID controller in term of time domain specification. The goal of PID controller design is to determine a set of gains: Kp, Ki, and Kd, so as to improve the transient response and steady state response of a system as: by reducing the overshoot; by shortening the settling time; by decrease the rise time of the system. Modified PID is the combination of classical PID in addition to Genetic Algorithm. Genetic algorithm consists of three steps: selection, crossover, and mutation. By using Genetic algorithm we correct the behavior of quadcopter.

scholarly journals Pid Controller Design for Multiple Time Delays System

2021 ◽  
Vol 15 ◽  
pp. 121-127
Author(s):  
Asma Karoui ◽  
Rihem Farkh ◽  
Moufida Ksouri
Keyword(s):  
Pid Controller ◽  
Time Delays ◽  
Controller Design ◽  
Multiple Time ◽  
Multiple Time Delays ◽  
Pid Controller Design ◽  
The Stability ◽  
And Control ◽  
Time Invariant

This paper presents an approach of stabilization and control of time invariant linear system of an arbitrary order that include several time delays. In this work, the stability is ensured by PI, PD and PID controller. The method is analytical and needs the knowledge of transfer function parameters of the plant. It permits to find stability region by the determination of p K , i K and d K gains.

Optimal fuzzy PID controller design for an active magnetic bearing system based on adaptive genetic algorithms

2014 ◽  
Vol 24 (5) ◽  
Author(s):  
HUNG-CHENG CHEN
Keyword(s):  
Genetic Algorithm ◽  
Pid Controller ◽  
Controller Design ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Adaptive Genetic Algorithm ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Pid Controller Design ◽  
Amb System

We propose an adaptive genetic algorithm (AGA) for the multi-objective optimisation design of a fuzzy PID controller and apply it to the control of an active magnetic bearing (AMB) system. Unlike PID controllers with fixed gains, a fuzzy PID controller is expressed in terms of fuzzy rules whose consequences employ analytical PID expressions. The PID gains are adaptive and the fuzzy PID controller has more flexibility and capability than conventional ones. Moreover, it can be easily used to develop a precise and fast control algorithm in an optimal design. An adaptive genetic algorithm is proposed to design the fuzzy PID controller. The centres of the triangular membership functions and the PID gains for all fuzzy control rules are selected as parameters to be determined. We also present a dynamic model of an AMB system for axial motion. The simulation results of this AMB system show that a fuzzy PID controller designed using the proposed AGA has good performance.

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