This Paper investigates the mean to design the reduced order observer and observer based controllers for a class of delayed uncertain nonlinear system subjected to actuator saturation. A new design approach of wavelet based adaptive reduced order observer is proposed. The proposed wavelet adaptive reduced order observer performs the task of identification of unknown system dynamics in addition to the reconstruction of states of the system. Wavelet neural network (WNN) is used to approximate the uncertainties present in the system as well as to identify and compensate the nonlinearities introduced in the system due to actuator saturation. Using the feedback control, based on reconstructed states, the behavior of closed loop system is investigated. In addition robust control terms are also designed to attenuate the approximation error due to WNN. Adaptation laws are developed for the online tuning of the wavelet parameters and the stability of the overall systems is assured by using the Lyapunov- Krasovskii functional. A numerical example is provided to verify the effectiveness of theoretical development.