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PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design
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DOI：10.3390/mi7090168.png)
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摘要
En 中文
Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO)-based algorithm and the evolutionary programming (EP) algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.
Keyword:
particle swarm optimization (PSO)-based
evolutionary programming (EP)
integral of the squared error (ISE)
micro air vehicle (MAV)
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