The application of photovoltaic (PV) systems increases dramatically since it is clean, sustainable, and easy to maintain and can be applied on transportation, phone application, on and off-grid energy production, satellite systems, and in any portable device that require energy. However, Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power point (MPP), which depends on environmental factors, such as temperature and irradiation. In order to continuously harvest maximum power from the solar panels, maximum power point tracking (MPPT) plays an important role for PV power pumping systems because it optimizes the power output for a given set of conditions. This thesis performs design and performance analysis of fuzzy sliding mode control (FSMC) for MPPT PV water pumping system. The proposed method controls the duty ratio of a DC-DC boost converter to produce maximum power from the solar panel and hence the speed induction motor could rotate with its maximum capacity and more water quantity is obtained. In this work mathematical modeling of the whole components such as PV panel, DC-DC Boost converter, DC-AC inverter, and the induction motor is individually modeled and then the proposed controller is designed in MATLAB/ SIMULINK. These individually modeled components and controllers are connected to generate 24KW power from the PV array and the performance is assessed under different environmental conditions. The performance of the controllers has been evaluated under uniform irradiation& temperature, rapidly varying irradiation, sudden change of ambient temperature, and the sudden variation of load. The performance of the sliding mode control (SMC), fuzzy logic control (FLC), and FSMC controllers for photovoltaic water pumping systems is evaluated through simulation studies and compared. The proposed MPPT techniques are able to track the MPP with the highest efficiency under dynamic and steady-state conditions. Based on the simulation result FSMC has an MPPT efficiency of 99.13% compared with 80.21% in FLC and 97.81% in SMC. Keywords: Boost converter, Fuzzy logic control, FSMC, MPPT, Photovoltaic (PV), Sliding mode control