| Active Disturbance Rejection Controller(ADRC) has the advantages of simple structure, easy-realized, highly precise, strong robustness. It is able to estimate and compensate the uncertainties and external disturbances in real time. At present, it has been widely used in robotics, magnetic suspension, missile flight attitude, tank fire control and inertial navigation and so on. However, in practical application, too many parameters,unknown tunning range and direction make it difficult to set parameters and limits the usage of ADRC. So in this paper, a Particle Swarm Optimization(PSO) algorithm is provided to solve the problem.This paper mainly studies the parameter optimization of ADRC based on particle swarm optimization and its application in the quad-rotor unmanned helicopter control system. The main content is as follows:Firstly, this paper introduces the principle of ADRC and analysises its three main components. According to the characteristics of ADRC algorithm, based on modular modeling theory, we create a custom module library with the M_Function design,S_Function design and subsystem packaging technology, which saves the modeling time and provides a platform for the algorithm research. And the simulation results show the strong robustness and disturbance rejection capability of ADRC.Secondly, in the practical applications of ADRC, there are many parameters and their values are difficult to adjust. While this paper uses PSO algorithm to set the parameters,which gets rid of the dependence on experience and manual tunning. In the end, the effectiveness of this optimization algorithm is proved through simulation experiment.Finally, use PSO-ADRC algorithm into quad-rotor unmanned helicopter control system which with the feature of underactuation, multivariable and strong coupling. On the established quad-rotor simulation platform, the PSO- ADRC algorithm has been tested and the results show its effectiveness in quad-rotor attitude control. |
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