In the analysis of wastewater treatment plants (WWTPs), it is very general to use ideal sensors and actuators without noise and delay for the measurement of dissolved oxygen, flow rate, ammonia, and nitrate levels. However, to control WWTPs in practice, non-ideal sensors and actuators only exist, and hence evaluation by considering non-ideal sensors is required. It is important to assess the performance of the advanced control strategies under non-ideal conditions and it is addressed in this research. Biological WWTP model such as benchmark simulation model (BSM1-P) with activated sludge process of ASM3bioP is used in the present study. In this chapter, non-ideal sensors with delay and noise and different combinations of sensors are analyzed. Three control strategies are designed (Proportional integral (PI) controller, Model predictive controller (MPC), and Fuzzy logic controllers (FLC)) to check the effluent quality and operating costs. For the right dissolved oxygen and nitrite monitoring assessment, the significance of delay and noise in sensors are much higher, as for ideal sensors a good control performance is achieved by increasing the controller gain. A total of nine different sensor class combinations are studied. MPC has shown an improved effluent quality of 3.6% in the sensor class combination of DO–B_O and NO–B_O. Fuzzy is not responding well to the sensor class combinations and there are no improvements. Operational cost is improved by 1% in the sensor class combination of DO–D_O and NO–D_O in the application of PI controller.