Practical Modeling and Comprehensive System Identification of a BLDC Motor

Abstract

The aim of this paper is to outline all the steps in a rigorous and simple procedure for system identification of BLDC motor. A practical mathematical model for identification is derived. Frequency domain identification techniques and time domain estimation method are combined to obtain the unknown parameters. The methods in time domain are founded on the least squares approximation method and a disturbance observer. Only the availability of experimental data for rotor speed and armature current are required for identification. The proposed identification method is systematically investigated, and the final identified model is validated by experimental results performed on a typical BLDC motor in UAV.

Modelling and attitude control of novel multi-ducted-fan aerial vehicle in forward flight

“…According to the real-time requirements, and the convenience of the experimental process with considering the controller's weight, size, vibration characteristics, power consumption, heat dissipation, scalability, input, output port configuration, a PC104 architecture computer was used as the airborne computer. The airborne computer obtains and analyses all kinds of the flight data supplied by airborne sensors on aerial vehicle, including the attitude angle and the attitude angular velocity (Xiang et al, 2015). Then it operates the designed control law, records and saves flight data, at the same time communicates with the ground station, receives instructions from a remote controller or the ground station, and feedbacks the real-time status information of the aerial vehicle to the ground station.…”

Four-Channel Teleoperation with Time-Varying Delays and Disturbance Observers

“…Then the stability of the whole teleoperation system does not depend on Φ ( ) and depends essentially on the stability of the feedback loop in Figure 4. Therefore, from (17) and Figure 4, = −Π −1 and = − Π −1 = − , which can be represented in a compact form in Figure 5(a). (14)- (17) and directly represented by Figure 4 and transformed into Figure 5(a) by Proposition 10.…”

“…Therefore, from (17) and Figure 4, = −Π −1 and = − Π −1 = − , which can be represented in a compact form in Figure 5(a). (14)- (17) and directly represented by Figure 4 and transformed into Figure 5(a) by Proposition 10. Let ( ) be as defined in (23) and let ( ) be as defined in [19] A sufficient condition for stability of the delayed system as described in Figure 5(a), with a complex diagonal structured uncertainty, is…”

“…In this work, because we know that force observers can be included using the concept of disturbance observer (DOB) [15][16][17], also called reaction force observers (RFOB) [18], to cope with unmeasured human or environmental forces, we adapt two DOBs (master and slave) to our generic framework for robust stability, by representing them as stable, fast filters affected by the uncertainty in the plant modelling. Our main result is an SSV test to verify robust stability for four-channel teleoperation with time-varying delays and disturbance observers.…”

Spectrogram Analysis: An Approach to Identify The Quadrotor Thrust Model

“…For a rotor-speed estimation, one can use the mathematical model of the propeller system, and then validate it with a tachometer sensor. In [6] an identification technique determines the brushless DC-motor parameters of RC helicopters and quadrotors. Rotary encoder and hall sensors inform respectively the rotor-speed and the required current.…”