Unmanned aerial vehicle flight control system parameter optimization method based on particle swarm optimization algorithm

Abstract

The invention provides an unmanned aerial vehicle flight control system parameter optimization method based on a particle swarm optimization algorithm, and the method comprises the steps: transmitting parameters to a cascade PID controller in an ArduPlane flight control system through an iteration method and the particle swarm optimization algorithm, and after the flight control and software exchange emulator complete a setting task together, enabling the cost value module to calculate the state cost and the energy cost of flight control in the process, transmitting the final cost value to the particle swarm algorithm, enabling the particle swarm algorithm to update the individual optimal value and the population global optimal value of each particle according to the newly obtained cost, and obtaining and transmitting new parameters to the ArduPlane module until iteration is finished. According to the method, the problem of parameter optimization of the cascaded PID controller in the flight control system is solved, the cascaded controller is optimized at the same time, the optimized parameters obtained by using the particle swarm optimization can ensure that the input energy loss of the controller is as small as possible, and the comprehensive performance of the controller is greatly improved.

Description

technical field [0001] The invention relates to a parameter optimization method of a flight control system of an unmanned aerial vehicle based on a particle swarm algorithm, and belongs to the technical field of automatic control. Background technique [0002] Due to its excellent performance and modular integration, fixed-wing UAVs are widely used in military, commercial and academic research fields. It is a 4-input 6-degree-of-freedom under-excited coupled nonlinear dynamic system, so the control system of the fixed-wing UAV is very complicated. [0003] In order to simplify the analysis process of the nonlinear system model, people often linearize the UAV model, and the simplified model system also simplifies its control system. The UAV control system is called the flight control system. ArduPilot is a world-renowned open source UAV flight control system, which contains open source control modules for various unmanned systems, including fixed-wing UAVs, rotor UAVs, unman...

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Problems solved by technology

[0005] In order to solve the above problems, the present invention proposes a parameter optimization method of the unmanned aerial vehicle flight control system based on the particle swarm algorithm, and utilizes the particle swarm algorithm to solve the parameter optimization of the cascaded PID controller in the fixed-wing unmanned aerial vehicle ArduPlane flight control system problem, freeing people from the tedious work of parameter adjustment, so that the complex cascaded PID controller in the flight control system can still automatically adjust the parameters

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