Algorithms for adaptive control with limited disturbance compensation

Abstract

This paper proposes an adaptive control scheme for systems affected by parametric uncertainty and limited external disturbances, without requiring measurements of the controlled variable's derivatives. The control approach provides compensation for these disturbances, addressing control problems with a reference model. Adaptive control is a technique where a system's parameters are adjusted based on external conditions or internal changes. In the context of constrained disturbance compensation, control algorithms must account for limitations on available resources or system capacity to counteract disturbances. Such algorithms can be beneficial in situations where the system has limited resources or where disturbances cannot be fully eliminated. The proposed adaptive control scheme aims to effectively manage systems subject to parametric uncertainty and bounded external disturbances, without the need for derivative measurements of the controlled variable. The control approach compensates for these disturbances, making it suitable for applications where complete disturbance rejection is not feasible due to resource or capacity constraints.