About Flight Mechanics
Flight mechanics is a branch of aerospace engineering that studies and assesses a flight vehicle’s motion with respect to a chosen frame of reference. It concerns on how to design and control the characteristic of the motion of flight vehicle with respect to its center of gravity, and of the vehicle’s center of gravity along its flight path within the designated mission. Also, here we conduct research in Astronautics, which focuses on how spacecraft can be launched and operated, covering discussion from Low Earth Orbit to interplanetary mission.
Our research group develops mathematical models and state-of-the-art flight control systems for aerospace engineering applications, primarily for novel unmanned aircraft configurations, satellite launch vehicles, and satellites.
Our main research includes (but not limited to):
- Flight simulators and mathematical modeling.
- Autonomous control and guidance system.
- Avionics and sensor systems.
- Aircraft performance, flight testing, and identification.
- Satellite sensors and actuators, trajectory and attitude control.
Flight Simulation and Mathematical Modeling
Mathematical Model and Simulation of Quadrotor UAV
Faculty involved: Dr. Yazdi I. Djenie.
Quadrotor, one of the most popular type of civil UAV, has been commercially existed in various sizes and prices. This popularity, however, has yet to be coupled with a proper method in mathematical modeling, design, and analysis. This paper describes a mathematical modelling process of a quadrotor UAV, using the similar methodology used in modelling a conventional aircraft. The process aims to result in a state space format, with a linear description of forces and moments acting on the vehicle, while maintaining accuracy of its dynamic tendencies. A 6 Degrees of Freedom mathematical model for the quadrotor in its hover mode is elaborated, starting from the general equation until the state-space form, along with the linearization assumptions. Afterward, the model is analyzed its stability and controllability via common method in flight dynamic and control.
Implementation of Turbulence Model for Flight Test Simulation
Faculty involved: Ony Arifianto, Ph.D.
Turbulence is a movement of air on small scale in the atmosphere that caused by instabilities of pressure and temperature distribution. Turbulence model is integrated into flight mechanical model as an atmospheric disturbance. Common turbulence model used in flight mechanical model are Dryden and Von Karman model. In this research, only Dryden continuous turbulence model were used. Dryden continuous turbulence model has been implemented, referring to the military specification MIL-HDBK-1797. The model was implemented into MATLAB/Simulink. The model will be integrated with flight model to observe the response of the aircraft when it’s flying through turbulence field. The turbulence model is characterized by multiplying the filter which is generated from power spectral density with band-limited Gaussian white noise input. In order to ensure that the model provide a good result, model verification has been done by comparing the implemented model with the similar model that is provided in aerospace blockset. The result shows that there are some difference for 2 linear velocities (vg and wg), and 3 angular rate (pg, qg and rg). The difference is instantly caused by different determination of turbulence scale length which is used in aerospace blockset. With the adjustment of turbulence length in the implemented model, both model result the similar output.
Autonomous Control and Guidance System
Obstacle Avoidance Algorithm
Faculty involved: Rianto A. Sasongko, Ph.D.
An avoidance algorithm is proposed in this research which works by generating avoiding waypoints, within the original predefined waypoints, when the vehicle finds obstacles obstructing its flightpath. The approach developed here bases the search for avoidance path on the utilization of ellipsoid geometry as a restricted zone containing the obstacle. The restricted ellipsoid zone is established by considering the identified obstacle geometry information, and further the ellipsoid becomes the basis for computing the new waypoints for avoiding the obstacle. These avoiding waypoints determined by computing the contact points between the ellipsoid and planes the normal vector of which are corresponded to the vehicle velocity vector. The information about geometry and dimension of the ellipsoid are computed from the information about obstacle geometry, which is assumed to be available, either from mission database or predicted from UAV’s ground detection system. In the development process, the algorithm is constructed in MATLAB environment and then simulated and analyzed in some scenario cases representing possible situations when an UAV has to avoid obstacles during its flight. This algorithm is intended to be integrated into the guidance system of UAV.
Aircraft Performance, Flight Testing, and Identification
Take off Simulation and Analysis of Aircraft with Twin Floats
Faculty involved: Toto Indriyanto, Ph.D.
Amphibious aircraft is a multi-function aircraft which can be operated on land and water. This type of aircraft helps transportation sector due to its ability to reach remote areas. Indonesia as the largest archipelago in the world has problems in connecting remote areas. Land transportations and conventional aircraft have difficulties to reach remote areas due to lack of facility. Hence, small aircraft capable of operating on land or water with take off and landing distance less than 1000 m are required. This study conducted take off simulation and analysis for DHC-6 Twin Otter Series 400 equipped with twin float. It tries to propose a simpler method to initiate the analysis of take of performance for float planes with limited data constraints. Several programs were used to generate required data, such as DatCom and SolidWorks. Float plane take-off simulation used in this research utilized Gudmundsson’s method. Results showed that the method is suitable and correctly produce take off distance and time similar to those of the real aircraft. Aircraft weight and thrust affect take-off distance and required time, as well as hydrodynamic forces produced. Reduction of weight 10% reduces the distance approximately 17%, while 10% thrust reduction increases take off distance about 15%. In the future this research will be expanded to include other float shapes and sizes, as well as flying boats.
Determination of UAV pre-flight Checklist for flight test purpose using qualitative failure analysis .
Faculty involved: Hendarko, S.T., M.Sc.
Safety aspects are of paramount importance in flight, especially in flight test phase. Before performing any flight tests of either manned or unmanned aircraft, one should include pre-flight checklists as a required safety document in the flight test plan. This paper reports on the development of a new approach for determination of pre-flight checklists for UAV flight test based on aircraft’s failure analysis. The LAPAN’s LSA (Light Surveillance Aircraft) is used as a study case, assuming this aircraft has been transformed into the unmanned version. Failure analysis is performed on LSA using fault tree analysis (FTA) method. Analysis is focused on propulsion system and flight control system, which fail of these systems will lead to catastrophic events. Pre-flight checklist of the UAV is then constructed based on the basic causes obtained from failure analysis.
Astronautics
Rocket Launch Modeling and Simulation with Thrust Vectoring Control and Scheduling
Faculty involved: Dr. Yazdi I. Jenie, Dr. Eng. Ridanto E. Poetro.
This research elaborates a mathematical model that is built specifically for simulating a launch of a multistage Launch Vehicle (LV) from the launch point to the orbit insertion. The dynamic model is built in MATLAB/Simulink environment that incorporates propulsion, aerodynamics, environmental, weight, and the engines with Thrust Vectoring Control (TVC), all in the six degrees of freedoms. The model also incorporated the multistage rocket simulation, where separation will immediately reduce masses and change aerodynamic characteristics. Falcon 9 LV, by SpaceX, is used as the research subject, in its operation to bring cargo to a parking orbit. Three simulation runs to test the model capability is conducted, including (1) open loop point mass simulation, (2) open loop full dynamic simulation, and (3) closed loop with TVC simulation. The final simulation shows conformity with the real LV launch data, suggesting that the model can be used as a base for control and launch schedule design.
Star Sensor Development
Faculty involved: Dr. Eng. Ridanto E. Poetro.
The use of star sensor, which is the most accurate attitude sensor on satellites, began to penetrate into micro satellites and nano satellites. Thus the need arises to research and develop star sensor independently to meet the specific design of micro satellites and nano satellites. There are mainly three approaches in star sensor research: digital simulation, hardware in the loop simulation, and field test of star observation. In digital simulation approach, all of processes are done in a software, including star image simulation. Hence, it is necessary to develop star image simulation software which could simulate real space environment and various star sensor’s configuration. This research focuses on star image simulation results done in various parameters: resolution, defocus level, stars’ magnitude limit, background noises, FOV, unexpected objects and missing stars. Those parameters are needed to test stars pattern recognition’s robustness. The results show that the star image simulation is able to simulate all those parameters.
