Experimental Analysis and Affirmation of Vital Parameters of Multi-Rotors Drones

Abstract: Trajectory tracking of micro UAVs requires accurate thrust and velocity estimates. High-quality motion control of quadrotors typically employs accurate high-speed optical sensing indoors. However, these measurements are not available outdoors, and GPS is unreliable and inadequate for performance motion control. We have developed small embedded force sensors that mount between a micro UAV's airframe and motors—forces generated by the rotors are measured as they are transmitted to the rigid body of the aircraft. The direct force measurements can be directly integrated with a model of the mapping between aircraft motion and induced rotor forces. From this, the translational velocities of the rotors relative to the local wind can be measured, and thus the overall velocity of the aircraft can be inferred. We have assembled a proof-of-concept quadrotor platform with all four rotors fitted with force sensors, and demonstrate accurate measurement of a quadrotor's lateral velocity during prescribed motions using the onboard force sensors. The vertical velocity measurement was found to be insensitive.

Abstract: In agricultural tasks, monitoring of large fields is required. In the last years automatic/autonomous monitoring has been researched; where unmanned aerial vehicles (UAV)—commonly known as drones—are used. For these systems, constrains related with autonomy during flight arise. In order to control properly the UAVs during flight, they require to measure physical variables, in a fast and accurate way. Also, the weight of instruments must be reduced for improving autonomy. In general, aerial vehicles obtain parameters like position, velocity and acceleration using inertial navigation systems. Regarding to this concern, in this work application of a novel technique for measurements onboard UAVs—particularly inertial measurement unit or IMU—is proposed. There are accelerometers inside the IMU. These accelerometers have a frequency domain output. The speed and position are calculated by the INS from acceleration. The acceleration is obtained from frequency measurements of the accelerometers output. For this reason an accurate and fast frequency measurement method is required. In this work, for this particular application, frequency measurement using principle of rational approximations is proposed. This technique allows to measure frequency in short time and with high accuracy, using a few electronic components. Due this properties, it perfectly fits requirements for UAVs.

Abstract: This work addresses the design and implementation of a filter that estimates the orientation of the body-fixed $z$ axis and the velocity of a quadrotor UAV from the inertial measurement unit (IMU)given a known yaw. The velocity and attitude estimation is possible since the filter employs a linear drag model measuring the drag forces on the quadrotor through the IMU. These forces are functions of the robot's velocity and attitude. In addition, the filter estimates the linear drag parameters and thrust coefficient for the propellers. These parameters may be fed back into a controller to improve tracking performance. Experimental results are used to validate the proposed approach.

Abstract: In this paper, a simple and easily applicable model of the coaxial propulsion unit for multirotor UAVs is presented. Measurements performed on the experimental test bench provided information about the generated thrust in relation to PWM control signals and supply voltage. Modelling techniques based on Takagi-Sugeno fuzzy interface and surface fitting are proposed. Implementation of the first order inertial element with the varying time constant allows to consider the propulsion unit's dynamics. A fuzzy model was chosen for implementation taking into consideration a computational complexity benchmark. Fusion of four independent models provides information about a total thrust generated by the physical platform during real flight scenarios. Promising results of experimental studies open the way for possible applications of the presented method, such as expanding estimation algorithms of attitude and vertical velocity or improvement of the mathematical model.

Abstract: In this work, we apply an adaptive observer for estimating the thrust generated by the individual rotors of a quadrotor UAV with uncertain actuator parameters, using a linear dynamic model of the system. In most of the previous works, the implementation of quadrotor control is based on the assumption of a known static relationship between the voltage signal to the motors and the thrust generated by the actuator-propeller assembly. However, due to variations in this voltage-to-thrust relationship, this approach may lead to undesirable results in practice. Feedback of the quadrotor thrust in the control system can provide more robustness to the system. In the absence of accurate knowledge of the actuator parameters, we use an adaptive observer for thrust estimation in this work. An adaptive observer is an algorithm for joint estimation of states and unknown parameters of a dynamical system. We use the adaptive Luenberger observer using two different cost functions, and apply a genetic algorithm to select the design parameters of the observer. We use low- and higher-order models for the actuator with the adaptive observer, and compare their performance. The results show that the estimates from the adaptive observer used with a low-order actuator model match the thrust values obtained from measurements with good accuracy.