*2.1. Description of the Proposed Method*

Fortunately, the interface of python is provided by AMESim. Python is a powerful, well-scalable program language in artificial intelligence. It has a lot of libraries for scientific analysis and optimization, which are easy to use. Therefore, a model-based intelligent optimization method with python is proposed in the present study. The model of an EHA driving a flight control surface is carried out by AMESim. The developed python script can generate design parameters by using an intelligent search method, and transfers them to the AMESim model. Then, the python script can run a simulation of the AMESim model with a pre-defined motion and load scenario of the control surface. The python script also can get the results when the simulation is finished, which can be used to evaluate the performance as the objective of optimization. Therefore, using the proposed intelligent design method cannot only greatly save labor costs, but also shorten the system development time.

The flow chart of the developed intelligent optimization method is shown in Figure 2. The intelligence MOO method will update the parameters, based on the search algorithm, to get the optimal solutions by iteration until the Pareto front of the design is obtained. The entire intelligent MOO design process can be described as:


**Figure 2.** Flowchart of the intelligent optimization design process, based on python.
