The descriptor Markovian jump systems ( DMJSs ) with partially unknown transition probabilities ( PUTPs ) are studied by means of variable structure control. First, by virtue of the strictly linear matrix inequality ( LMI ) technique, a sufficient condition is presented, under which the DMJSs subject to PUTPs are stochastically admissible. Secondly, a novel sliding surface function based on the system state and input is constructed for DMJSs subject to PUTPs; and a dynamic sliding mode controller is synthesized, which guarantees that state trajectories will reach the pre-specified sliding surface in finite time despite uncertainties and disturbances. The results indicate that by checking the feasibility of a series of LMIs, the stochastic admissibility of the overall closed loop system is determined. Finally, the validity of the theoretical results is illustrated with the example of the direct-current motor. Furthermore, compared with the existing literature, the state convergence rate, buffeting reduction and overshoot reduction are obviously optimized.