Concerning multiphase batch processes with delays, disturbances, and actuator faults, the design of 2D robust hybrid composite iterative learning fault-tolerant guaranteed cost controller is put forward. First, a hybrid iterative learning control law is introduced and the multiphase batch process with interval time varying delays is converted to an equivalent 2D-FM switched system with actuator faults by the introduction of system output tracking errors and state errors and consideration of fault effects. Next, a sufficient condition for satisfying asymptotical stability that the closed-loop switched system has the upper bound of minimum performance index is established by application of the theoretical framework of 2D system and selection of 2D Lyapunov Krasovskii function on the basis of an average dwell time method. Then, the optimal design algorithm of the 2D hybrid robust iterative learning fault-tolerant guaranteed cost control is presented. In the meantime, in view of the effects of delay terms on system stability, the constraint condition that the closed-loop system makes steady operation and has the optimal control performance where the system encounters actuator failure faults within the allowed fault coverage is constructed, and the design scheme of the control law is provided. In the end, key variables in the injection and packing phases in the injection molding process are controlled to further verify the effectiveness of the proposed method.