Subject to limited computational resource, feedback scheduling aims to improve, or to optimize, the global control performance of real-time control systems. For the system that consists of simple control tasks, a feedback scheduling scheme is presented to shorten tasks’ deadlines online as much as possible, so as to reduce jitter and to improve the performance. For the system that consists of complex control tasks, another feedback scheduling scheme is presented to adjust the reserved processor time for each task dynamically, and thus to optimize the performance, if these tasks can be implemented as anytime algorithm. The general feedback scheduling architecture is introduced. The control strategy in both schemes is model predictive control. The designs of feedback controllers are discussed. And the stability conditions are also analyzed.