| Actuator failure compensation is an important topic of both theoretical and practical significance. Actuator failures in control systems may cause severe system performance deterioration and even catastrophic closed-loop system instability. For system safety and reliability, such actuator failures must be properly accommodated.; Actuator failures are uncertain in nature. Very often it is impossible to predict in advance which actuators may fail during system operation, when the failures occur, what types and what values of the failures are. It may also be impractical to determine the failure parameters after a failure occurs. Adaptive control, which is capable of accommodating system parametric, structural, and environmental uncertainties, is a suitable choice for designing actuator failure compensation schemes without explicit knowledge of the occurrences of actuator failures and the failure values.; This dissertation research is focused on adaptive control of linear time-invariant (LTI) systems with unknown actuator failures characterized by some unknown inputs being stuck at some unknown fixed values. The objective is to develop a theoretical framework for adaptive control of linear systems with plant parameter and actuator failure uncertainties, guaranteeing system stability and tracking performance.; In this work, we address several adaptive actuator failure compensation problems. We first investigate the state tracking problem for LTI systems with unknown plant dynamics and actuator failures and a state feedback design is developed. We then study the output tracking problem for minimum phase LTI systems with both unknown plant parameters and actuator failures. Several designs are presented: a state feedback design and an output feedback design for single-output systems and two output feedback designs for multi-output systems. All the four designs are based on the model reference adaptive control (MRAC) approach. Finally, we develop an output feedback output tracking scheme for single-output systems based on the adaptive pole placement control (APPC) approach, which is applicable to both nonminimum phase and minimum phase systems.; For each design, a parameterized controller structure is first proposed, and the design conditions for plant-model matching are studied. Under the design conditions, the proposed controller structure is effective in achieving the desired plant-model matching when implemented with matching parameters. (Abstract shortened by UMI.)... |
