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In order to realize texture image segmentation, a new texture segmentation method is presented. The method fused with Local Binary Pattern (LBP), Gray-level Co-occurrence Matrix (GLCM) and permutation entropy. After processing the texture image by the rotation invariant LBP operator, the LBP image can be obtained. Then co-occurrence matrixes can be calculated in the LBP image, some features which...
Abstract-Wind farms are considered to be negative loads from the point of view of a utility. As installed capacity of wind power retains a significant proportion of generation mix in the electric system, operators have the increasing expectation that wind turbines should function in some way similar to the conventional plants. This paper presents a control strategy to regulate active power for different...
LAPES (Low Altitude Parachute Extraction System) is one of the three methods used for Aerial Delivery. It can transport the cargos, weapons and equipments to the front fast. However, it also makes a high demand to the aircraft. The drop sequence's low altitude allows for no margin for pilot error and a plane crash is real dangerous. This paper takes the cargos which are moving in the aircraft or falling...
The focus of this paper is on nonlinear adaptive inversion control system of a longitudinal hypersonic vehicle model with neural network compensation for uncertain effects. Considering the partially unknown model dynamic for hypersonic vehicle, and the adaptive dynamic inversion control method with neural network compensation is presented, which can compensate the hypersonic vehicle model errors by...
In this paper we present a new technique for design of nonlinear feedback controllers that yield satisfactory tracking performance for a class of dynamic systems. The controller is based on minimization of predicted tracking errors. Some tracking convergence properties of the controller are established. In the face of model uncertainties, we show that the unique structure of the controller allows...
A new optimal nonlinear feedback control law is obtained for the minimum-energy control problem of robots. The result can lead to a better design of robust feedback control when the problem is solved by the nonlinear programming approach. Supporting numerical examples are presented.
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