Journal
EVOLUTIONARY INTELLIGENCE
Volume 14, Issue 1, Pages 61-73Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s12065-019-00312-8
Keywords
Quadrotor; PID controller; Optimization; Stochastic nature-inspired algorithm; Evolutionary algorithms
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This study investigates the control of a quadrotor using a PID controller. By designing a control structure and tuning controller parameters with stochastic nature-inspired algorithms, efficient path tracking performance is achieved. A comparison study between different optimization algorithms shows slight differences in the achieved performance.
This paper aims to investigate the control of a quadrotor by PID controller. The mathematical model is derived from Euler-Lagrange approach. Due to nonlinearities, coupling and under-actuation constraints, the model imposes difficulties to generate its controller by using classic ways. Firstly, we have designed a control structure which weakens the couplings and permits to develop a decentralized control. Secondly, in order to get the optimal path tracking, the controllers' parameters were tuned by stochastic nature-inspired algorithms; Genetic Algorithm, Evolution Strategies, Differential Evolutionary and Cuckoo Search. A comparison study between these algorithms according to the path tracking is carried out by implementing simulations under MATLAB/Simulink. The results show the efficiency of the proposed strategy where the optimization algorithms achieve good performance with a slight difference between the indicate techniques.
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