Title: Fractional Order Control of A Fixed-Wing UAV
1Fractional Order Control of A Fixed-Wing UAV
- Haiyang Chao, Ying Luo, Long Di
- Advisor Dr. YangQuan Chen
- CSOIS
- Utah State University
- 2009/01/23
2Outline
- Introduction to UAV Flight Control Fractional
Order Control Techniques. - Problem Statement of UAV Flight Control.
- System Identification of UAV Roll-loop Model.
- Roll Loop Control of UAV Using Fractional PI
Control. - Simulation of FOC Control of UAV.
- Experimental Validation of FOC on a Fixed Wing
Small UAV. - Future Time Line.
3Introduction to UAV Flight Control
- The UAV market has grown rapidly this decade
including both military and civilian
applications. It is estimated that the global UAV
market will reach around 7.2 billion for 2009
1.
In courtesy of 1.
In courtesy of 1.
4Introduction to UAV Flight Control
- Most UAVs can be treated as flying sensors to
investigate a specified area from a certain
altitude. UAV flight control system plays a key
role here not only for the flight stability
issues but also for the sensor data
interpretation part. For example, the UAV control
performance can affect the georeferencing result
of aerial images a lot. - There are several special requirements for UAV
flight control - Robustness Consideration.
- Winds, especially gusts can affect the small UAVs
a lot. - Different flight conditions including weather,
altitude. - Various Payloads.
- Hand-made airframes without accurate modeling.
- Limited Resource Constraints
- Limited accuracy for on-board inertial sensors.
- Limited computational power.
- Limited size weight
- Anything else????
5Introduction to Fractional Order Control
Techniques
- Fractional order control (FOC) is attracting lots
of interests recently. - FOC introduces fractional derivative and
fractional integral and provides more solution
candidates for the control problem. - PIAlpha ( ) controller is one of the
simplest fractional order controllers similar to
the classical proportional integral (PI)
controller. - FOC can give advantages over traditional
controllers because FOC has a larger memory and a
wider solution selection range.
6Contribution
- Achieve more accurate trajectory tracking for our
small fixed-wing UAV. - Give a more robust solution to the UAV control
problem. - Test the discrete fractional order controller on
a real system to show that FOC works in the real
world. - Test the performance of fractional 0rder
controller for a highly coupled nonlinear system.
7Problem Statement of UAV Flight Control
8UAV Flight Control Basics
- UAV dynamics can be modeled using 12 system
states - Position longitude, latitude, altitude
. - Attitude roll, pitch, yaw
- Gyro rate roll rate, pitch rate, yaw rate
- Air speed
- Angle of attack and slide-slip angle
- UAV control inputs generally include aileron,
elevator, rudder, and throttle. - So the UAV dynamics can be modeled using
nonlinear equations.
9UAV Dynamic Model
- Dynamic model with 6-degree of freedom 2.
In courtesy of Austin Jensen.
10UAV Dynamic Model
- Dynamic model with 6-degree of freedom.
In courtesy of Austin Jensen.
11UAV Flight Control Basics
- The nonlinear dynamic model is hard to analyze.
However, it can be linearized at some trimming
point and treated as a simple SISO or MIMO linear
system so that linear system theories can be
used. - The UAV 6 degree of freedom dynamics can be
decoupled to two modes - Longitudinal mode pitch loop.
- Lateral mode roll loop.
- The roll loop control problem or lateral dynamics
is carefully studied in this paper.
12Roll-Loop Control of UAVs
- The roll loop of a UAV can be treated as a SISO
(roll-aileron) system after it achieves a steady
state flight. - The steady state flight means all the force and
moment components in the body coordinate frame
are constant or zero. It can be treated as a
singular point or equilibrium point. - An intuitive controller design is classical
proportional integral and derivative control
(PID).
13System Identification of UAV Roll Loop
14System Identification of Roll-loop
- Non-parametric method transient response
- Impulse response analysis
- Step response analysis (FOPTD)
- Square response analysis
- Parametric method
- Linear model
- ARX
- Least square parameter identification using PRBS
excitations.
15System Excitations PRBS
- PRBS stands for pesudo random binary sequence.
- PRBS is good because its signal is rich in all
the specified frequency. - PRBS signal length 2N-1, N 1,2,3
- Example PRBS signal with the length of 255.
16System Identification Using Square Wave Response
- Steiglitz-Mcbride iteration method.
- Stmcb() in matlab.
17Roll Control of UAVs Using Fractional PI
Controller
18Fractional Order PI Controller Design for UAV
18
19Fractional Order PI Controller Design for UAV
19
20Fractional Order PI Controller Design for UAV
- Amplitude and phase of FOPI first order model
of UAV
20
21Fractional Order PI Controller Design for UAV
- Amplitude and phase of FOPI controller
21
22Fractional Order PI Controller Design for UAV
- Amplitude and phase of the open loop system
22
23Fractional Order PI Controller Design for UAV
- FOPI controller design principle
23
24Fractional Order PI Controller Design for UAV
- FOPI controller design principle
24
25Fractional Order PI Controller Design for UAV
25
26Fractional Order PI Controller Design for UAV
26
27Simulation of Roll-loop Fractional PI Control of
UAV
Ref 2.
Ref 3.
28Simulation Platform Aerosim
- Aerosim is a nonlinear 6 degree of freedom
simulink model for mid-size UAV aerosonde 3. - This tool is developed by Marius Niculescu from
u-dynamics. - All the simulink blocks are achieved through dll.
- Simulink minimal step 0.02 s.
29Simulation Platform Aerosim
30UAV Sys ID in Time-domain
- Use time domain system identification
- stmcb(y_ip(11800 12100),x_ip(11800 12100),0,1)
- System model identified 1.147/(s 0.9793)
31PID Control of Roll-loop
32Fractional PI Control of Roll-loop
33Controller Design
- PI Controller Using Modified Ziegler-Nichols
Method - Kp 0.2601 Ki 28.4091 Kd 0
- Fractional Order PIalpha controller Using Flat
Phase Method - Kp 0.5503 Ki 28.31 alpha 1-0.111
34Case 1 Wind Gust Disturbance
- Wind disturbance input v_n,0,0
35Case 2 Gain Margin
36Case 2 Gain Margin
37Experimental Validation of FOC on Small Fixed
UAVs
38UAV Sys ID of 72 UAV
- Use time domain system identification using 10 hz
data and data interpolation algorithm - stmcb(y_ip(11800 12100),x_ip(11800 12100),0,1)
- System model identified 1.147/(s 0.9793)
39UAV Sys ID of 60 UAV
- Use time domain system identification using 10 hz
data and data interpolation algorithm - Stmcb() x_min 544, x_max 578
- data_processing_gx2_pprz_plot_interpolation_200901
15.m - System model identified 0.8887/(s 0.7314)
40Fractional Order PI Controller Design for UAV
- Identified Roll control model of our 72 UAV
40
41Fractional Order PI Controller Design for UAV
- Numerical curves following the designed
specifications
41
42Fractional Order PI Controller Design for UAV
- Verify the numerical method by the Bode plot
42
43Fractional Order PI Controller Design for UAV
- Simulation Implementation of the fractional
operator
Oustaloup Algorithm is used to realize the
fractional operator approximately here
43
44Experimental Validation of FOC
- Based on the structure under the Box Frac Der
s0.1, we are able to write it in a form as
follows
45The continuous and discrete form of s0.1
- We need to convert this form from continuous
domain to discrete form, which can be
accomplished using a MATLAB function C2D - After choose the sampling time as 1/60 and the
method as tustin, we are able to get the
following form in Z domain
46After adding a integrator, why not directly use
s-0.9 instead of using 1/ss0.1
- The comparisons of s-0.9 and 1/ss0.1
47Some explorations
- Given Kp0.5503,Ki28.31, a-0.111
- The Plant1/(1/13.76s1)
- Vstep10
48The continuous and discrete form of the
fractional order I
- The transfer function in discrete domain
- The final format used for C code
49Problems dragging us from real flight tests
- Synchronization issue, big impact on system
Identification
- When we convert the transfer function from
continuous domain to discrete domain, some
information get lost
50Future Timeline
- Solve the problem of log synchronization.
- Before next Wednesday.
- Haiyang Dee.
- Solve the problem of FOC discretization.
- Before next Wednesday
- Ying Luo Haiyang
- Write C code for FOC with parameters
pre-specified. - Before next Wednesday
- Haiyang Ying Luo.
- FOC flight test preparation.
- Before next Thursday
- Haiyang, Dee Ying luo.
- Write C code for any PIalpha controller.
- Before Feb. 4th.
- Haiyang Ying Luo.
- FOC parameter online tuning.
- Before Before Feb. 4th.
- Haiyang Ying Luo.
51Reference
- 1 http//www.defenseindustrydaily.com/a-54b-uav-
sector-from-20062016-02592/ - 2 http//www.aerosonde.com
- 3 http//www.u-dynamics.com
- 4 Ying Luos paper.