Unmanned helicopter control optimization method based on particle swarm algorithm

Abstract

The invention relates to an unmanned helicopter control optimization method based on a particle swarm algorithm, and belongs to the field of unmanned helicopter explicit model tracking control. The method comprises the following steps: determining an unmanned helicopter explicit model control system to obtain an integral constant matrix G4 and a gain diagonal matrix R; g4 and R being used as parameters in the particle swarm to be optimized through a particle swarm algorithm, and outputting a controller. According to the method, the particle swarm optimization algorithm is introduced into the explicit model control method, parameters in the unmanned helicopter controller are optimized, the control quality of the unmanned helicopter is improved, and the robustness of a controlled object is improved. The obtained controller can enable the performance of the controlled object to be optimal in a constraint range, the design is simpler, and the use is more flexible. The method also solves the disadvantage that the selection of the integral constant matrix G4 and the gain diagonal matrix R in the traditional explicit model tracking control method depends on expert experience through a trial and error method, so that the G4 and the R can be constructed more conveniently and the optimal controller can be obtained.

Description

technical field [0001] The invention belongs to the technical field of unmanned helicopter control, and in particular relates to an unmanned helicopter control optimization method based on a particle swarm algorithm. Background technique [0002] Unmanned helicopter (UMH for short) not only has the advantages of convenient deployment, flexible maneuverability, no casualties and strong survivability, but also has the advantages of fixed-point hovering, vertical take-off and landing, and flight in any direction. ability. The flight dynamics characteristics of unmanned helicopter are high-order and strong coupling. Coupling is the main factor affecting the handling quality of an unmanned helicopter during flight. The explicit model-following control system (model-follow control system, MFCS) can effectively reduce coupling and improve flight quality. The explicit models of the four channels established by MFCS are linear independent models. Through the design of the tracking...

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Problems solved by technology

For the design of G4 and R matrices, the trial and error method is generally adopted. The controller designed in this way not only requires a large workload, but also does not necessarily guarantee that the controller can achieve a good control effect.

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