Gain scheduling linear model of an electro-hydraulic actuator

In different industrial processes in which position and force control are desired, electro-hydraulic systems have a widespread area of utilization. Models of electro-hydraulic systems include high order nonlinearity. In this study, a gain scheduling linear model corresponded with nonlinear model of a hydraulic force actuator system is developed. The proposed model is constituted in two distinct and consecutive stages. In the first step, nonlinear terms caused to nonlinearity are described by the means of measurable or observable system parameters and embedded in a nonlinear scheduling parameter. Thus, the scheduling parameter is continuously extracted from main system. In the second step, the nonlinear system equation is rearranged by the scheduling parameter and by this way parameter varying linear model is obtained. The simulations which are performed by use of Matlab-Simulink computer program show that the proposed model rightly fits to the nonlinear system model.

Fractional differentiation-based observability analysis method for nonlinear X-ray pulsar navigation system

In the traditional observability analysis methods, only current and a few historical measurement values are considered. For the linear systems, the satisfactory analysis results can be obtained. However, for the nonlinear systems, the analysis results are not completely in accordance with the navigation errors since the high-order nonlinearity of the navigation system is not embodied on the observability matrix. In order to solve this problem, a fractional differentiation-based observability analysis method is developed. Considering the fact that the fractional differentiation with respect to time is characterized by long-term memory effects, the fractional derivative of the measurement model with respect to time is considered. By this means, more historical measurement data can be exploited. And then the fractional differentiation-based observability matrix, which reflects the high-order nonlinearity of the navigation system, is constructed. Finally, as the condition number is not directly proportional to the positioning error, to evaluate the navigation performance, the exponent weighted condition number is developed, where small condition numbers have large weight. The simulation results demonstrate that the fractional differentiation-based observability analysis method is sensitive to the orbital elements in the nonlinear X-ray pulsar navigation system, and has small calculation load. In addition, compared to the traditional observability analysis methods, it is observed that its analysis result matches well with the X-ray pulsar navigation performance.