A surrogate-assisted multi-objective optimization method for preliminary design of horizontal tail control system

The decision of a multi-disciplinary preliminary design scheme based on engineering experience requires multi-departmental designers to spend a long time for calculation, verification, discussion, and consensus-building. This article proposes a surrogate-assisted multi-objective optimization method for efficient horizontal tail control system preliminary design. A multi-objective optimization model for horizontal tail control system is established, and the surrogate-assisted methods and BP neural networks are used to construct the implicit objective function. The recommended preliminary design scheme is derived from the Pareto solution set of the optimization model. And a collaborative optimal solution evaluation principle is proposed to select the scheme concisely. A horizontal tail control simulation model is built to examine the performance of the preliminary design scheme. The results show that the recommended scheme has an excellent performance in terms of the design goals.