Maximum Power Point Tracking and Output Power Control on Pressure Coupling Wind Energy Conversion System

Maximum Power Generation Control of a Hybrid Wind Turbine Transmission System Based on H∞ Loop-Shaping Approach

“…In [7], piecewise affine models were proposed to approximate a nonlinear hydraulic wind power transfer system. Experimental and simulation studies were conducted to demonstrate the accuracy of the [8], a combined method was proposed for wind energy conversion system using pressure coupling hydrostatic transmission. A PID controller and an adaptive fuzzy sliding mode controller were designed to control the generator speed.…”

Application of Electro-Hydraulic Actuator System to Control Continuously Variable Transmission in Wind Energy Converter

“…where ϕ is half of the increase in the wrapped angle on the primary pulley. Substitute Equations (9) and (10) into Equation 8, one can obtain:…”

“…This has been an appealing research trend around the world [6][7][8][9]. The wind speed always varies, but the conventional wind system can only produce the power within "cut in" and "cut out" of the wind speed [10]. There are several methods that can be control the speed, such as pitch control, stall control, yaw control, and combinations of the above methods [11,12].…”

A Neural Network Based Sliding Mode Control for Tracking Performance with Parameters Variation of a 3-DOF Manipulator

“…However, up to now, formulating controllers satisfying control performance and the stability of the system is still a big challenge due to its high nonlinearity, coupling dynamics reactions, and uncertainties [1]. In order to deal with these problems, many approaches such as using a proportional integral derivative (PID) control [2], feedback linearization [3], robust control [4,5], adaptive control [6][7][8], backstepping (BSP) control [9,10], hybrid proportional derivative sliding mode control (PDSMC) [11], sliding mode control (SMC) [12][13][14][15] and even intelligent control [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] have been studied.…”

“…Jun et al [17] integrated adaptive laws to determine the parameters of the FLS and then used FLS to approximate switching gains and eliminate the chattering. The FLS, whose laws were designed based on some knowledge about the control system [18], has been successfully applied to many linear and non-linear systems [19,20]. In such studies, the FLS with adaptive laws were employed to adjust controller gains of the SMC.…”