Energy Harvest of Multiple Smart Sensors With Real-Time Fault-Detection

For multiple smart sensors with limited energy supply, the relationship between the energy supply and sensor fault-free region is often unknown, and neither of the interior structure nor exterior circumstance modeling the smart sensors is easy to accurately achieve, so how to guarantee the fault-free smart sensors to harvest the most energy in the fault-free way is a very challenging topic. To address this issue, this paper first formulates the individual smart sensor as a single-input single-output (SISO) model-free system (MFS), with its energy supply and sensing error as the input and output, respectively, then makes use of Lyapunov function to deduce an upper bound of the fault-free region to realize the fault-detection of any smart sensor and disclose the relationship between the energy supply and fault-free region, and finally achieves the optimal energy supply guiding the overall energy harvest of all fault-free smart sensors to converge to the maximum with the convergence rate no larger than
$\kappa $
,
$\kappa \in [{0,1}]$
, while enjoying the real-time fault-detection. An algorithm based on the sound theoretical foundations is further proposed to implement the optimal energy supply. Theoretical analysis, simulations and field experiments jointly verify the performance of our method. To our best knowledge, it is the initial work towards this issue. Note to Practitioners—This paper addresses the interesting issue of how to guarantee multiple smart sensors to harvest the most energy in the free-fault way. Through the insightful disclosure of relationship between the energy supply and sensor fault-free region, and the optimal control of energy supply, this paper facilitates the overall energy harvest of all fault-free smart sensors that work under the environments, where the available energy is limited, to converge to the maximum while enjoying the real-time fault-detection, which we believe could push the development of Internet of Things (IoT) or Cyber-Physical System (CPS) that employs multiple smart sensors to sense the physical world. Simulations and field experimental investigations jointly show that the proposed solution outperforms the existing solutions.