Abstract
In recent decades, micro air vehicles driven by electric propellers have become a hot topic, and developed quickly. The performance of the vehicles depends on the rotational speed of propellers, thus, improving the accuracy of rotational speed measurement is beneficial to the vehicle’s performance. This paper presents the development of a soft sensor for the rotational speed measurement of an electric propeller. An adaptive learning algorithm is derived for the soft sensor by using Popov hyperstability theory, based on which a one-step-delay adaptive learning algorithm is further proposed to solve the implementation problem of the soft sensor. It is important to note that only the input signal and the commutation instant of the motor are employed as inputs in the algorithm, which makes it possible to be easily implemented in real-time. The experimental test results have demonstrated the learning performance and the accuracy of the soft sensor.
Highlights
Extensive studies of micro air vehicles (MAVs) driven by electric propellers have been carried out
This study aims to develop a soft sensor for the rotational speed measurement of an electric be detected
An adaptive learninga algorithm for the soft measurement sensor by using This study aims to develop soft sensor isforderived the rotational speed of an Popov electric hyperstability theory, based on which a one‐step‐delay adaptive learning algorithm is further propeller
Summary
Extensive studies of micro air vehicles (MAVs) driven by electric propellers have been carried out. An estimation method which takes measured terminal voltages and currents as input is proposed This which methodtakes is based on theterminal model reference identification achieve. Kalman estimator [13], and a sensors based onadaptive various nonlinear observers,state suchobserver as an adaptive mode observer [11], an adaptive nonlinear [14], can useful estimator for solving speed measurement nonlinear observer state observer [12], be an extended Kalman [13],rotational and a nonlinear observer [14], problems. An adaptive learninga algorithm for the soft measurement sensor by using This study aims to develop soft sensor isforderived the rotational speed of an Popov electric hyperstability theory, based on which a one‐step‐delay adaptive learning algorithm is further propeller.
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