A novel condition for stable nonlinear sampled-data models using higher-order discretized approximations with zero dynamics. (May 2017) - Zeng, Cheng; Liang, Shan; Xiang, Shuwen
Abstract: Continuous-time systems are usually modelled by the form of ordinary differential equations arising from physical laws. However, the use of these models in practice and utilizing, analyzing or transmitting these data from such systems must first invariably be discretized. More importantly, for digital control of a continuous-time nonlinear system, a good sampled-data model is required. This paper investigates the new consistency condition which is weaker than the previous similar results presented. Moreover, given the stability of the high-order approximate model with stable zero dynamics, the novel condition presented stabilizes the exact sampled-data model of the nonlinear system for sufficiently small sampling periods. An insightful interpretation of the obtained results can be made in terms of the stable sampling zero dynamics, and the new consistency condition is surprisingly associated with the relative degree of the nonlinear continuous-time system. Our controller design, based on the higher-order approximate discretized model, extends the existing methods which mainly deal with the Euler approximation. Abstract : Highlights: A novel consistency condition which improves some well-known results is derived. The relation between exact discretized plant and high-order model can be obtained. The new consistency condition is surprisingly associated with the relative degree.