High-precision response of the surrogate model is desired in the process of optimisation. An excessive number of sampling points will increase the cost of the calculation. The appropriate number of sampling points cannot only guarantee the accuracy of the surrogate model but also save the calculation cost. The purpose of this research is to demonstrate the eventuality of using an adaptive surrogate model for optimisation problems. The adaptive surrogate model is built on an adaptive sampling approach and an extended radial basis function (ERBF). The adaptive sampling is an approach that new sampling points are placed in the blank area and all the sampling points are uniformly distributed in the design region using Multi-Island GA. The precision of the ERBF surrogate model is checked using standard error measure to determine whether the surrogate model should be updated or not. This adaptive surrogate model is used to optimise a cruise missile head shape. Aerodynamic and stealthy performance of the cruise missile head shape are considered in this research. Different global objective function and different weight factor are used to research the aerodynamic and stealthy performance in this optimisation process. The results show that the drag is reduced with a slender head shape and the radar-cross section (RCS) value is reduced with a short head shape.

The purpose of this research is to prove the eventuality of using a novel adaptive surrogate model for optimization problems. The adaptive surrogate model is based on iteration sampling and extended radial basis function (ERBF). This method improves the precision by a means that new sample points is placed in the blank area and all the sample points is uniformly distributed in the design region. The precision of the surrogate model is checked using standard error measure to determine whether updating the surrogate model or not. Since the prediction of modal frequencies require structure modal simulations. In order to decrease the number of computer simulations, a Multi-Island GA approach is combined with the adaptive surrogate model to find the optimum modal frequencies of a strapdown inertial navigation system for electric helicopters. The strapdown inertial navigation system is comprised of damping material, counterweight material and inertial navigation sensor. This is a multi-objective functions optimization problem since the modal frequencies are considered from mode 1 to mode 6 in this paper. Several weights of multi-objective functions are utilized to research the modal frequencies. The whole number of 15 sampling points is picked to build the primary surrogate model using Latin hypercube sampling (LHS). The results of adaptive surrogate model show that two new sampling points are needed to reform the precision of the surrogate model under the condition of 2 % confidence bounds. The structure modal optimization results show that the choice of the weights for the multi-objective functions has a major effect on the final optimum modal frequencies. Time-and frequency-domain analysis indicated that the optimum modal frequencies are far away from the excitation frequencies to avoid strapdown inertial navigation system resonance as far as possible.

Offshore wind power industry develop rapidly in recent years. Offshore wind has many advantages compared with onshore wind turbine. For example, it do not take up land and can make better use of the sea wind resources. However, the flexible components of wind turbines violent vibration will cause the fatigue damage and increase the cost of the maintenance and reduce the service life. Pitch variable is an effective means of control to prevent the sea wind of the interference. In recent years, robust control has won a bigger development. In the paper a multi-objective pitch control strategy based on robust theory is proposed for large wind turbines. The experimental results shows that the robust ∞ H control has a good effect on the wind turbines variable pitch control.