ABSTRACT
Over the past decades, discussions on the robust stability and stabilization problem are rich in control system literature. As well as known, time-delay and parameter uncertainties often occur in many dynamic systems and are frequently a cause of instability and performance degradation (Gao et al. 2008). The main task is to design a controller which is not only stable but also guarantee an adequate level of performance. One design approach to this problem is called guaranteed, cost control approach, firstly presented by Chang and Peng. This approach is better to provide an upper bound to a given cost function, therefore, the system performance degradation incurred by the uncertainties is guaranteed to be less than this bound (Jiang
et al. 2008). Based on this advantage, lots of significant results have been obtained for the discrete-time case and the continuous-time case. In the recent years, these approaches have been extended to uncertain nonlinear systems. Although these approaches have proven to be efficient in solving various control problems, the guaranteed cost sampled-data control problem for uncertain nonlinear systems have no much work to been done yet (Fredman 2010). This is the objective of this paper.
