Abstract
While synthesizing optimal control algorithms for complex objects, the computation load is essential; therefore, deriving control laws in analytical form is important. Since different optimality criteria are used while synthesizing optimal control laws, the effectiveness of the derived algorithms may vary significantly depending on the operating conditions and modes. Thus, optimal synthesizes based on the joint maximum principle allow considering of control actions constraints and deriving an algorithm which is optimal in terms of speed. However, the discrete nature of control actions leads to the sliding mode. Algorithms, which use the predicting model method, based on the Krasovsky’s functional do not result in sliding mode; therefore, resulting accuracy of the control is higher comparing to the joint maximum principle method. However, the range of control actions change is considerable and it will take more time to achieve control objectives. The paper presents an algorithm for fuzzy control of angular velocities of an axisymmetric aircraft, which bases on control actions accumulation and defuzzification. The algorithm combines the joint maximum principle and the predicting model methods. Presented modeling results confirm the effectiveness of the proposed approach.
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Trofimenko, V. (2021). Fuzzy Controller for Angular Velocities of an Axisymmetric Aircraft. In: Radionov, A.A., Gasiyarov, V.R. (eds) Advances in Automation II. RusAutoCon 2020. Lecture Notes in Electrical Engineering, vol 729. Springer, Cham. https://doi.org/10.1007/978-3-030-71119-1_75
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