Actuator faults greatly affect the performance and stability of control systems, an issue that is even more critical for systems required to operate autonomously under adverse environmental conditions, such as unmanned vehicles. To this end, passive fault-tolerant control (PFTC) systems can be employed, namely fixed-gain control laws that guarantee stability both in the nominal case and in the event of faults. In this paper, we propose a counterexample guided inductive synthesis (CEGIS)-based approach to design reliable PFTC policies for nonlinear control systems. Our approach takes into account actuator saturation, tackles both partial and total actuator faults, and employs a synthesis technique guaranteed to converge within finite-time. Extensive numerical simulations illustrate how the proposed method can be applied to realistic operational scenarios involving the control of velocity and heading of autonomous underwater vehicles (AUVs). Our PFTC technique exhibits comparatively short synthesis time (i.e. minutes) and requires low computational cost. These features render the presented method particularly suitable for embedded applications with limited availability of onboard energy and power resources.
Fault-tolerant control of nonlinear systems: An inductive synthesis approach
Masti, Daniele;
2026-01-01
Abstract
Actuator faults greatly affect the performance and stability of control systems, an issue that is even more critical for systems required to operate autonomously under adverse environmental conditions, such as unmanned vehicles. To this end, passive fault-tolerant control (PFTC) systems can be employed, namely fixed-gain control laws that guarantee stability both in the nominal case and in the event of faults. In this paper, we propose a counterexample guided inductive synthesis (CEGIS)-based approach to design reliable PFTC policies for nonlinear control systems. Our approach takes into account actuator saturation, tackles both partial and total actuator faults, and employs a synthesis technique guaranteed to converge within finite-time. Extensive numerical simulations illustrate how the proposed method can be applied to realistic operational scenarios involving the control of velocity and heading of autonomous underwater vehicles (AUVs). Our PFTC technique exhibits comparatively short synthesis time (i.e. minutes) and requires low computational cost. These features render the presented method particularly suitable for embedded applications with limited availability of onboard energy and power resources.| File | Dimensione | Formato | |
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