RECONFIGURABLE CONTROL SYSTEM FOR UNMANNED

AERIAL VEHICLES

OVERVIEWUNMANNED AERIAL VEHICLESFLIGHT MECHANICSCONTROL SYSTEMCONTROL ALGORITHMCONTROL SYSTEM SAFETYCONTROL SYSTEM FAILURE MODES ADVANTAGESREFERENCES

ReconfigurationReconfiguration in case of aerial vehicles

means that,the most critical functions,needed for vehicle controllability,can be taken over by another node of the system if the primary node fails.

Examples of reconfigurable autopilots are RAMA UAV,Yamaha RMAX R-UAV etc..

UNMANNED AERIAL VEHICLES Unmanned Aerial vehicle also known as

UAS(Unmanned Aircraft System)

UAS is the term introduced by the Federal Aviation Administration (FAA) & adopted by United States Department of Defense (DOD) & Civil Aviation Authority(UK)

High altitude aircraft controlled by personnel on ground. Generally used for scientific/commercial research missions

The earliest unmanned aerial vehicle was Hewitt-Sperry Automatic Airplane after World War 1.

The modern Remote Piloted Vehicle (RPV) era began in 1959

UAV consist of Unmanned Aircraft(UA), the Control System & other related support equipment.

It also called Drones, Remotely Piloted Vehicle (RPV).

Example:- RQ-7 SHADOW, RQ-5 HUNTER, RQ-11 RAVEN etc.

control system used in UAVsRAMA UAV control system.

RAMA stands for Remotely Operated Aerial Model Autopilot.

It is a universal ,lightweight,and compact autopilot for small UAVs.

It is an open project,held at the Department of Control Engineering,Faculty of Electrical Engineering of the “Czech Technical University in Prague”.

A Rotorcraft UAV equipped with the RAMA system

Flight MechanicsTwo reference frames-

Earth frame,body frame.xyz-Earth frame,XYZ-

body frameX,Y,and Z axes are

sometimes called roll(θ),pitch(Φ) and yaw(Ψ) axes of the vehicle.

Conversion from one frame to another is given by rotation matrix R=R1.R2.R3

Control System block diagram

Control AlgorithmThe vehicle control algorithm had been designed

to control a rotorcraft UAV. Five separate layers. Angular Rate Control Layer ( ARCL)- is

responsible for the angular rates stabilization in the three vehicle axes.

Attitude Control Layer( ACL)- serves for the attitude stabilization,

Velocity Control Layer (VCL)-controls the vertical and horizontal velocities of the vehicle.

Position Control Layer(PCL)-is used to stabilize the vehicle position in space.

Trajectory Tracking Layer (TTL) is responsible for the vehicle guidance along a pre-set trajectory.

Control Algorithm Layered structure

Control System SafetyUAV control system is undoubtedly a critical

system, and must have a reasonable safety margin to be of any practical use.

An out-of-control UAV might cause property damage.

RAMA is designed so that for most of the failures, there is an appropriate Failure Mode the system can engage, in order to preserve the critical functions for the sake of some high-level functionality loss.

The only critical node of the system is the Servo Control Unit (SCU), whose complete failure would definitely lead to grave consequences.

Partial or complete failure of any other system part (the MCC, DAM, or some/all of the sensors) would lead to the loss of some functionality, but would definitely preserve the semi-automatic or at least fully manual control of the vehicle.

Control System Failure modesMCC Failure Modes:In case of the MCC failure the only viable solution is to

put the Servo Control Unit (SCU) into the Manual Control Mode (MCM).

In this mode, the SCU takes over the direct control of the actuators and runs unaffected by the rest of the system.

It ignores any commands possibly coming from the faulty MCC or other nodes and actuates the control surfaces directly according the control stick positions.

State diagram of RAMA’s failure modes

Navigation Unit Failure modesThe Data Acquisition Module (DAM) failure

makes the system enter the Manual Control Mode (upon the pilot’s command).

Failure of any of the sensors is detected by the DAM.

A possible DAM restart after the watchdog reset would only take about 50 ms, which is fast enough compared to the vehicle dynamics.

Role of MCC in NUThe DAM failures are detected by the MCC.

An unexpected DAM reset is monitored and reported by the MCC.

SCU Failure ModesThe Servo Control Unit (SCU) failure would

inevitably lead to the vehicle loss.The system would enter the Critical Failure

Mode (CFM).SCU is equipped with a watchdog timer,

ensuring a restart in the case of a microcontroller hang up. A full restart of the SCU is fast enough (it takes about 50 ms, much like the DAM restart).

Communication Failure ModesIn case of a data communication loss the

telemetry data packets are stored in a buffer and sent off-line as soon as the data link is re-established.

Failure of the wireless control link would currently make the system enter the Critical Failure Mode.

Power Failure ModesCurrently, there are no Battery Failure Modes

- both batteries must be in good shape to keep the system running.

2 batteries-ACB (Actuator Battery),AVB (Avionics Battery).

A re-design of the SCU is considered, then the SCU able to run from either battery, so it can drain power from the Actuator Battery (ACB), should the Avionics Battery (AVB) fail.

SISO PID Controller StructureRAMA currently utilizes SISO (Single Input Single

Output) PID controllers at all levels of control.The controller parameters are as follows:k, i, d, m - Proportional, Integral, Derivative and

Feed-Forward gains b, c - Reference weighting coefficients for

proportional and derivative components w - Reference filter cut-off frequency n - D filter cut-off frequency h - Sampling period

ADVANTAGESControl systems that are fitted in UAVs has got

strict weight, low power consumption, and price limitations.

A necessary redundancy for the most critical functions can be achieved due to the system reconfiguration and graceful degradation in case of a failure.

REFERENCES1. Ondˇrej Špinka, Ondˇrej Holub “Low-Cost Reconfigurable

Control System for Small UAVs” iEEE transactions on industrial electronics, vol. 58, no. 3, march 2011

2. O. Špinka, Š. Kroupa, and Z. Hanzálek, “Control system for unmanned aerial vehicles,” in Proc. 5th IEEE Int. Conf. Ind. Inf., 2007, pp. 455–460

3. B.Mettler, Identification, Modeling and Characteristics ofMiniature Rotorcraft,vol. ISBN 1-4020-7228-7. Dordtrecht, The Neteherlands: Kluver AcademicPublishers, 2003

4. B. Mettler, M. B. Tischler, and T. Kanade, “System identification modeling of a small-scale unmanned helicopter,” Journal of the American Helicopter Society,October 2001.

5. V. Gavrilets, B. Mettler, and E. Feron, “Nonlinear dynamic model of a smallsize acrobatic helicopter,” in Proc. of the AIAA Conf. On Guidance, Navigation and Control, Montreal, Canada, 2001.

6. A. Bogdanov, E. Wan, and G. Harvey, “SDRE flight control for X-Cell and RMax autonomous helicopters,” in Proceedings of the 43rd IEEE Conference on Decision and Control, December 2004.

7. J. Cham, “The Ph.D. Comics.” http://www.phdcomics.com

8. “The yamaha RMAX UAV website.” http://www.yamaha-motor.co.jp/global/industrial/sky/solution/rmax

9. “Paparazzi - The free autopilot.” http://paparazzi.enac.fr.

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