Automatic Landing of a UAV Using Model Predictive Control for the Surveillance of Internal Autopilot’s Controls

International Journal of Innovative Research in Advanced Engineering (IJIRAE) ISSN: 2349-2163
Issue 03, Volume 4 (March 2017) www.ijirae.com
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IJIRAE: Impact Factor Value – SJIF: Innospace, Morocco (2016): 3.916 | PIF: 2.469 | Jour Info: 4.085 |
ISRAJIF (2016): 3.715
IJIRAE © 2014- 17, All Rights Reserved Page -104
Automatic Landing of a UAV Using Model Predictive Control
for the Surveillance of Internal Autopilot’s Controls
Devika.M
Assistant Professor, Dept. of Electronics & communication Engineering
Sathyabama University, Chennai, India
Manuscript History
Number: IJIRAE/RS/Vol.04/Issue03/MRAE10096
Received: 03, March 2017
Final Correction: 20, March 2017
Final Accepted: 27, March 2017
Published: March 20
Abstract - The objective of this paper is to provide safe landing of an UAV on any demanding conditions and can be very
useful during the period of floods, rescuing the affected people. It can be also be useful in military operations. This system
provides stable method for landing of an aircraft. Image processing technique is used to capture the image and find the
angle of inclinations. MATLAB produces four types of image through Image processing technique. They are Gray
image, Edge Detection image, Histogram image, object detection image. MATLAB sends the histogram signal to
microcontroller using UART. It is used to convert the received parallel data into serial data for transmitting the
data to longer distance. Relay drives the DC motor. Angle of inclinations is measured according to the detected image of
the surface. MATLAB produces the total inclination value of the surface. DC motor automatically adjusts the landing gear
according to the obtained input inclination value of the surface. An UAV is programmed to adjust the landing gear
according to angle of inclination. When the landing surface is detected for landing the aircraft, it automatically adjusts the
landing gear and lands the aircraft according to the inclined surface of the landing area.
Keywords —MPC model, UAV, Image-processing, MATLAB
I. INTRODUCTION
Presently a-days, late progressions in handling capacities have empowered the likelihood of utilizing new computationally
immoderate control systems like the Model Predictive Control (MPC) on continuous applications. On this paper, a structure is
proposed for the configuration of a managing MPC to be actualized more than an easier, more solid inside circle PID Autopilot
without making any changes to its structure. The proposed framework had the capacity add new capacities to the inner circle
by making little remedies to its control requests, guaranteeing the agreeability with limitations. UAVs are basically air ship
without a human pilot inside. The heaviness of these vehicles can run from a couple of grams to 12 tons having 35 meters of
wingspan. We depict the utilization of model predictive control (MPC) utilizing state mapping to the programmed arriving
arrangement of a space plane. The controller must be intended to empower the vehicle to take after reference signals as for
direction and speed, which are communicated as capacities of the downrange. To track the reference flags, a control
data is by and large outlined so one or more perfect transient reactions are figured it out. We additionally have added to a flight
control framework in light of this idea. Nonetheless, it was not tasteful for utilization as the controller of a genuine vehicle
because of the absence of thought of the data and state requirements. A controller that considers these requirements can be
composed by applying MPC. Then again, it is hard to predefine the transient reactions important to track the reference signals,
which shift with the current downrange. In this paper, another methodology utilizing state mapping and criticism linearization
is proposed to enhance the control execution of following the reference signals. State mapping is inferred to portray a
framework in which the reference signs can be taken care of as a steady set point, and the portrayed framework is changed
utilizing state input. An unmanned elevated vehicle (UAV) is a flying machine furnished with an on - load up flight controller,
information preparing units, sensors, and correspondence framework, which make it fit for performing self-sufficient flight
missions in view of a prearranged flight information or driven remotely from a ground control station. This class of vehicles
offers more prominent profits over kept an eye on airplane when utilized for high -danger errands or in missions obliging high
secrecy. Quick advancement saw in the innovative work of UAVs can be credited to various components, for example,
mechanical progressions, political and financial elements among others. UAVs can be characterized into settled - wing and
rotorcraft.

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There is vast time defer in `man-on top of it' unmanned airplane vehicle (UAV) framework, particularly for remote
control flight by satellite correspondence. Time postponement has awesome effects on UAV and payload control, which can
prompt the framework shaky. Current autopilots have restriction, as they may experience circumstances where 3-D situating
data is lost or inaccessible. An alternate impediment is the requirement for path focuses to focus the following way to take after
to a sought destination, which the way directs ought to wind up troublesome toward place. It can't identify the article precisely
thorough survey of writing identified with rotorcraft UAV outline and advancement.
II. RELATED WORK
J.S.Santos [2] proposed that framework ID taking into account flight test information of the Vector-P Unmanned Aerial
Vehicle which performs the parameters estimation and model acceptance. UAVs are basically flying machine without a human
pilot inside. The heaviness of these vehicles can go from a couple of grams to 12 tons having 35 meters of wingspan, which
adds to UAVs research territory, expecting to present the element framework distinguishing proof of Vector-P UAV with flight
test information and perform an autopilot outline, utilizing the recognized model. With a specific end goal to perform the
airplane air movement optimized coefficients ID, it was utilized the parameter estimation system called Output Error Method,
which comprises in minimizing the yield mean squared slip of the real plant and the recognized model yield. The flight
information is utilized to gauge the longitudinal air movement optimized coefficients. F.A.de Almeida [3] described the
method to utilize the focus of fancied frequencies in which the brief time and phugoid mode is emphasized. Ideal time venture
for excitation is outline to give the data transfer capacity. A multistep 3-2-1-1 and doublet info are connected on lift meaning to
energize the longitudinal movement. The information procurement framework made by PC board and GPS, weight and inertial
sensor is utilized. Keeping in mind the end goal to perform the model approval, the Goodness of Fit criteria is connected to
confirm the deviation between the computational and genuine results. An elevation hold autopilot is composed utilizing the
recognized model and, finely, it is demonstrated a correlation between the elements conduct. This paper proposes that a flaw
tolerant flight control framework utilizing model prescient control (MPC). The proposed strategy, named doable target-
following MPC, channels the reference interest to ensure attainability of the compelled improvement. The inputs of the
framework recognizable proof system grew in this examination that is in light of Klussendorf project are numerical model
investigation, time venture for moves, known parameters, obscure parameters to be assessed, starting parameters, imperatives
parameters and systems to minimize the expense capacity esteem. This building design is additionally fit for redistributing, in a
stable way, the control endeavors among solid actuators, regarding their constraints. A direction following framework in view
of the proposed flaw tolerant model prescient controller is showed utilizing the ground test system of the VFW-614 ATTAS
(Advanced Technologies Testing Aircraft System), demonstrating attainability and satisfactory execution. R.J.M. Afonso [4]
proposed that Predictive Control plans can be composed with ostensible asymptotic dependability sureties gave that the related
advancement issue is possible at every inspecting time. Then again, model-plant confounds, outside annoyances or issues may
cause the advancement to wind up infeasible. Such an issue spurs the improvement of strategies went for recouping possibility
without disregarding hard physical limitations forced by the way of the plant. This paper researches the conceivable
favorable circumstances of utilizing an approach of set point administration to go around infeasibility issues in a Predictive
Control structure. The examination is principally concerned with strength of the controller in regards to actuator blames that
can be displayed as a change in the permitted outing of the control signal. The outcomes got with the proposed set point
administration method are contrasted with the default arrangement gave by the received computational tool stash if there
should be an occurrence of infeasibility. An application including a nonlinear reenactment model of a lab helicopter with three
degrees of opportunity is present.
III. SYSTEM STUDY
In this model, the image can be processed using MATLAB explained in the following schematic diagram.
Figure 1. Block diagram.
The Image of the surface is captured and is sent to PC for processing. The captured image is processed using Image Processing
technique in MATLAB. The processed image signal is converted to serial data to communicate longer distances with the help
of UART.

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ISRAJIF (2016): 3.715
Since Microcontroller cannot process the image signal, so the image signal is converted into Histogram signal and it is fed into
microcontroller using image processing. After that histogram signal is converted into angle of inclination and forward to the
relay driver with the help of micro controller. Finally, the landing gear is adjusted according to the angle of inclination of the
surface.
IV. PROPOSED MODEL
In this paper, the Image of the surface is caught and is sent to PC for handling. The caught picture is transformed utilizing
Image Processing procedure as a part of MATLAB.MATLAB methodologies the picture and produces four kinds of picture
sign. They are: 1) Gray Scale Image. 2) Edge Detected Image. 3) Histogram Image. 4) Angle of Inclination. They got
information picture is initially changed over into Gray Scale Image. At that point it recognizes the edge surfaces in the picture.
Since Microcontroller can't process picture flag, the picture sign is changed over into Histogram sign and it is encouraged into
microcontroller utilizing picture transforming. UART is utilized to change over parallel information into serial information to
convey to longer separations. Transfer switch is utilized to control a few circuits with one sign. DC engine is put on arriving
rigging and is utilized to modify the arriving apparatus agreeing of the slants. Capacitor is utilized to store vitality in the
framework. MATLAB discovers the edge of slants of every article recognized and discovers the aggregate slant estimation of
the surface. The system is composed to alter the arriving rigging in favored bearing. Installed C is utilized to program
Hardware segments of the circuit. A voltage controller is intended to consequently keep up a consistent voltage level. A
voltage controller may be a basic "food forward" configuration or may incorporate negative criticism control circles. It may
utilize an electromechanical component, or electronic parts. At last, the arriving apparatus is balanced by point of slant of the
surface.
V. EXPERIMENTAL RESULTS
From the above descriptions applies manually, we are getting the sample images. An example information picture is taken and
is prepared in MATLAB. They got picture is transformed and it is changed over into dark scale picture. The acquired dark
scale picture is then further transformed utilizing picture preparing technique. After changing over the first picture into dim
scale image, the MATLAB identifies the edges of the entire surface of the recognized. Since Microcontroller can't process
picture flag, the picture sign is changed over into Histogram sign and it is bolstered into microcontroller utilizing picture
processing. Angle of slant is discovered utilizing MATLAB and the sign is gone to the equipment part. The arriving
apparatus is balanced by acquired slanted worth. The slant qualities are figured by surface zone of the got picture and the
quantity of items detected. They got yield signal from MATLAB is nourished into the microcontroller utilizing RS232cable as
a part of the type of histogram sign.
Figure 2. Assumed input signal
The data signal is gotten in the microcontroller and is prepared further. Transfer is utilized commute the DC engine. Transfers
are utilized to control the sign from two or more circuits. DC engines are utilized to conform the arriving rigging as indicated
by the got signal.
Figure 3. Angle of inclination

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ISRAJIF (2016): 3.715
A UAV consequently distinguishes the suitable territory for arriving and terrains the vehicle. It naturally alters the arriving
apparatus as indicated by the plot of slant that is distinguished. It alters the arriving apparatus in two headings i.e. either in left
or right course. On the off chance that there is no point of slant distinguished they the arriving rigging stays same and grounds
the air ship.
VI. PERFORMANCE ANALYSIS
Figure 4. Graph for obtained inclination values
The above diagram demonstrates the estimations of slant in a measurement structure. The items are recognized by surface
territory of slant. A UAV consequently identifies the suitable region for arriving and grounds the vehicle as per the edge of
inclination.
VII. CONCLUSION
This work contributes an Automatic landing of a UAV using model predictive control for the surveillance of internal
autopilot’s controls is proposed. This work is utilized to give safe arriving of a UAV on any requesting conditions. A UAV
catches the picture of the arriving surface through Image preparing procedure. MATLAB process they got info picture flag and
discovers the plot of slants. MATLAB produces four kind of picture through Image transforming system. Initially Image –
Gray picture; Second Image – Edge Detection picture; Third Image – Histogram picture; Fourth Image – object
recognition picture Histogram sign is gone to the microcontroller utilizing UART. UART is utilized to change over the
approaching parallel sign into serial sign for exchanging information to longer separations. A voltage controller is utilized to
naturally keep up a steady voltage level. We portray the use of model prescient control (MPC) utilizing state mapping to the
programmed arriving arrangement of a space plane. A capacitor is a detached two- terminal electrical segment used to store
vitality electro- statically in an electric field. A resistor is a detached two- terminal electrical part that executes electrical
resistance as a circuit component. Hand-off is utilized commute the DC engine. Transfers are utilized to control the sign from
two or more circuits. DC engines are utilized to alter the arriving rigging as indicated by the got signal. DC engine modifies
arriving apparatus concurring they got signal from the transfer. A UAV naturally identifies the suitable zone for arriving and
consequently changes the arriving apparatus as per the edge of slant and terrains the lands the vehicle.
REFERENCES
[1]. Juliano A. de Bonfim Gripp, Ulisses P.Sampaio“automatic landing of a UAV using model predictive control for the
surveillance of internal autopilot’s controls”2014 IEEE transaction on unmanned aircraft systems may 27-30
2014.Oriando.FL,USA.
[2]. J. S. Santos and L.C.S.Goes,“System identification based on flight test data and auto pilot design for longitudinal
motion of the Vector- P UAV” at 22nd International Congress of Mechanical Engineering (COBEM 2013), November
3-7, 2013, Ribeir˜ao Preto, SP, on Brazil.
[3]. F.A.de Almeida, “Reference Management for Fault-Tolerant Model Predictive Control” at Journal of Guidance,Control,
and Dynamics,2011.
[4]. R. J.M. Afonso and R. K.H. Galvao, “Predictive Control of a Helicopter Model with Tolerance to Actuator Faults” at
Conference on Control and Fault Tolerant Systems, Nice, France in October 6-8, 2010

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