Wojciech Giernacki

Estimation of Altitude and Vertical Velocity for Multirotor Aerial Vehicle Using Kalman Filter

Knowledge about precise robot localization is a key ingredient in controlling it, but the task is not trivial without any visual or GPS feedback. In this paper, authors concentrate on estimation of information about the robot’s altitude. One of the ways to acquire it, is a barometer. This type of sensor returns atmospheric pressure from which the height above the sea level can be computed. These readings have some disadvantages e.i.: vulnerability to pressure jumps and temperature drift as well as delay on the output. These problems can be solved by using Kalman filter algorithm for estimating altitude and vertical velocity, based not only on barometer readings, but also on accelerometer data. In the paper, derivation of the Kalman equations for the process to estimated are shown. Also improvements of the algorithm are described. The results of tests of this algorithm on real flying robot proved that estimates calculated with this method are precise and noise resistant.

Performance of Coaxial Propulsion in Design of Multi-rotor UAVs

There are many different types of propulsion systems developed for multi rotor UAVs. One of the most interesting designs is so called X8 quadrocopter, which extends original quadrotor concept to 8 motors, arranged in 4 coaxial pairs. The advantage of this solution is increased lift of platform, with reasonable volume of platform kept. However, this design suffers from the loss of efficiency due to coaxial propellers’ configuration, because the lower propeller loses thrust working in prop wash of upper propeller. This paper presents the experimental verification of performance of such propulsion system in practical terms of designing multi rotor platforms, comparing to design with 8 isolated propulsion units. In addition, its advantages versus classic quadrotor concept is shown. The series of experiments with different motors and sizes of propellers were conducted to estimate efficiency of coaxial propulsion regarding useful thrust generated by each configuration.

Thrust estimation by fuzzy modeling of coaxial propulsion unit for multirotor UAVs

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 units 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.

Stability analysis and tracking performance of fractional-order PI controller for a second-order oscillatory system with time-delay

The main aim of this paper is to present the analysis of stability regions and tracking performance for the closed-loop system with second-order plant with time-delay and continuous fractional-order PI controller. It is a trial to extend the results and methodology presented in [11] to non-integer order systems. The tracking performance is based on two quality indices IAE and ISE. The tuning method of fractional PI controller is with respect to Hermite-Biehler and Pontryagin Theorems.

Mathematical models database (MMD ver. 1.0) non-commercial proposal for researchers

Mathematical Models Database (MMD) is an online repository of mathematical models that can be easily used for research purposes, in teaching or in performing comparative tests. In a single free-of-charge, freely accessible Internet service all the data from the database is available with an expected (in its final form) several ready-to-use models, either purely mathematical or physics-based. Apart from the models themselves there are also documents describing the background of their derivation included, references to bibliography for further reading where they have been used and numerous attachments, e.g. parts of the code, time plots, results of simulations, ready handouts, etc. Using a simple browser it is possible to constraint the search to selected classes of models. It is planned in the future to make MMD a platform where every interested researcher will be able to include their models. This should streamline the possibility of creating a single Internet site where models from a vast number of disciplines can be found, such as from the field of control engineering and robotics, electrotechnics, mechatronics, computer science, and other fields, even those not directly connected to the latter.

Unscented Kalman Filter for an orientation module of a quadrotor mathematical model

The article describes the Unscented Kalman Filter, used in an orientation module of the quadrotor. Control of the quadrocopter is an important issue. Since it belongs to the group of the UAVs (Unmanned Aerial Vehicle), quadrotor must pass safety requirements in order to be used in urban spaces. Here, authors are solving one of the most important problems: estimation of the state vector of the quadrotor. Multirotors like quadrotor can work in semi autonomous or full autonomous mode. Regardless of the used mode, at least one control loop must be always on: an orientation loop. Normally a regulator responsible for an orientation stabilization is based on measurements from IMU (Inertial Measurement Unit). Here, an extended version of the state estimator, based on IMU readings and prediction from the model is introduced. Authors have implemented the Unscented Kalman Filter (firstly described in [1]) and proved that, this estimator is suitable in case of UAV.

Robust CDM and pole placement PID based thrust controllers for multirotor motor-rotor simplified model: The comparison in a context of using anti-windup compensation

Positioning and orientation precision of a multirotor aerial robot can be increased by using additional control loops for each of the driving units. As a result, one can eliminate lack of balance between true thrust forces. A control performance comparison of two proposed thrust controllers, namely robust controller designed with coefficient diagram method (CDM) and proportional, integral and derivative (PID) controller tuned with pole-placement law, is presented in the paper. The research has been conducted with respect to model/plant matching uncertainty and with the use of anti-windup compensators for a simple motor-rotor model approximated by first-order inertia plus delay. From the obtained simulation results one concludes that appropriate choice of AWC compensator improves tracking performance and increases robustness against parametric uncertainty.

Robust estimation algorithm of altitude and vertical velocity for multirotor UAVs

This paper describes the process of the development and improvement of the altitude and vertical velocity estimation algorithm. The previous method was developed by authors two years back. After a diagnosis of pressure temperature drift caused by the main IMU, the additional barometric sensor was introduced. Based on readings from this reference component, three main modifications were developed to the algorithms structure. In addition, three experimental sequences are presented to compare the previous approach with new ones. Results showed that new methods achieve better performance and are free from pressure drift caused by sensors heating. Decreasing frequency of altitude measurements in Kalman filter resulted in more robust estimates for pressure changes not related to the vertical movement in indoor and outdoor flights. With properly working estimation algorithm, there is a possibility to develop a controller to maintain desired altitude or vertical velocity.

Introduction of the Flying Robots into the Human Environment: An Adaptive Square-Root Unscented Kalman Filter for a Fault Tolerant State Estimation in a Quadrotor

Recently, there have been growing interest in an autonomous control of Unmanned Aerial Vehicles (UAV). The key objective for scientists is to make the robots capable to operate in human shared environment. The main problem concerns control as well as filtering sensory data in all scenarios. Among many types of control algorithms there are a few which takes into account fault cases. The control algorithm can be fault tolerant in case of actuators saturation or their damage. The situation is more complicated in sensory system failure, in which case, the control is defenseless. In this article, a novel Adaptive Square-Root Unscented Kalman Filter (ASRUKF) in application of fault tolerant (FT) state estimator is presented. The SRUKF was designed for an orientation module of a quad rotors mathematical model. The emphasis was put on the estimators adaptability in case of the sensory system fault. The main objective of this paper was to show the idea of adaptability of the ASRUKF in terms of FT system. The work includes model derivation, explanation on the SRUKF algorithm as well as description of an adaptive parameters change of the estimator. Finally, the paper shows the experiment with a quad rotor in test bed and promising results.

An Efficient PSO-Based Method for an Identification of a Quadrotor Model Parameters

This paper considers the method of Quadrotor’s model parameters identification. Nowadays, restrictions are being imposed on the drons, forcing their control algorithms to be robust and faultless. This can be partially ensured by Model Reference Adaptive Control (MRAC) as well as dedicated state estimators (e.g. Extended Kalman Filter). Although those methods can be easy implemented and used, in all scenario, the parameterized model is needed. In this work we proposed the identification method for parameters of the quadrotor’s orientation model, based on the PSO (Particle Swarm Optimization). We also add different physical aspects to model, so it can characterize the real Quadrotor more precisely. The conducted experiments shows that the PSO, can provide fast and reliable estimation of the model parameters. It also reveals interesting nature of the proposed models.