Embed Size (px)
Citation preview
1
Ahmed CHEMORI
Laboratoire d’Informatique, de Robotique et de Microélectronique de Montpellier LIRMM, CNRS/Université de Montpellier
161, rue Ada 34095
www.lirmm.fr/~chemoriEmail : [email protected]
Ecole Nationale Supérieure d’Ingénieurs de Tunis
Module doctoral : Modélisation et Commande Avancée des Robots
SEMINAR 1 March, 21st 2018
Speaker : Ahmed CHEMORI 2
LIRMM laboratory at Montpellier, France
LIR
MM Montpellier
Department of
Computer science
Department of
Robotics
Department of
Microelectronics
Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM)
444 : 215 permanent staff and 170 PhD students, 60 administration staff in 3 departments
• At 10 km from the Mediterranean sea
• More than 300 sunny days / year !
1220
Speaker : Ahmed CHEMORI 3
University of Montpellier
LIR
MM
Speaker : Ahmed CHEMORI 4
Robotics department at LIRMM
LIR
MM
Robotics
Department
DEXTER
IDH
ICARDEMAR
EXPLORE
ROB / INFO
5 Research Teams :
Image and interaction for manipulation of visual data Human sensory motor system (modelling, control, neuroprosthesis)
Speaker : Ahmed CHEMORI 5
Experimental facilities
LIR
MM
Speaker : Ahmed CHEMORI 6
My research activities in Robot Control
LIR
MM
ROBOT
CONTROL
Marine
Robotics
Humanoid
Robotics
Wearable
Robotics
Parallel
Robotics
Underactuated Robotics
http://www.lirmm.fr/~chemori
Speaker : Ahmed CHEMORI 7
Outline of the presentation
Out
line
Introductiona) Robotics today
Context and problem formulation
Our experimental platform
Stabilization control problema) Control problem formulation
b) Proposed control solutions
c) Real-time experimental results
Limit cycle generation control problem a) Control problem formulation
b) Proposed control solutions
c) Simulation & real-time experimental results
Conclusion
Speaker : Ahmed CHEMORI 8
Introduction
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 9
Today robotics is a very riche field with wide range of applications :
. . .
Robotics today
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 10
Context & Problem Formulation
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 11
PendCon AcrobotAdept Viper S650 Barrett Wam
6 degrees of freedom
6 actuators 2 degrees of freedom
1 actuator
6 degrees of freedom
7 actuators
Fully actuated
Nbr Act = DOF
Underactuated Redundant
Nbr Act < DOF Nbr Act > DOF
Context & problem formulation
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 12
Context & problem formulation
4 illustrative examples
2 DOFs Versus 1 Actuators
Example 1 : The AcrobotIntroduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 13
Context & problem formulation
4 DOFs Versus 1 Actuators
4 illustrative examples
Example 2 : The triple inverted pendulumIntroduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 14
AV-8B Harrier PVTOL
Context & problem formulation
4 illustrative examples
Example 3 : The PVTOL
3 DOFs Versus 2 Actuators
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 15
Context & problem formulation
4 illustrative examples
Example 4 : The Cubli
6 DOFs Versus 3 Actuators
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 16
Systems with less actuators than degrees of freedom
Two sources of under-actuation :
Decided in the design stage Minimize the cost, the weight, consumption, etc
Because of the deficiency of one/more actuators.
Context & problem formulation
3 DOFs Versus 3 Actuators 3 DOFs Versus 2 Actuators
X
Fully actuated Underactuated
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Nonlinear coupling between actuated and unactuated coordinates
Internal dynamics often unstable Non minimum phase Systems
Speaker : Ahmed CHEMORI 17
PVTOL
Acrobot/Pendubot Flexible arms Walking robots
Underwater vehicles Surface vehicles
Context & problem formulation
Some other examples
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 18
Inertia wheel inverted pendulum
The Schilovski Gyrocar (1914)
Brennan monorail (1903)
It is an old idea !
(2016)
Context & problem formulation
Ford Gyrocar
(1961)
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 19
Other examples using a gyrostabilizer
Aerospace
[Townsend et al 2007] Marine systemsIK
UR
A A
UV
ECP 750Academic
Cu
bli
(ETH
)
Context & problem formulation
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 20
Context & problem formulation
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Other examples using a gyrostabilizer
Speaker : Ahmed CHEMORI 21
Our Experimental Platform
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 22
Experimental setup
Inclinometer
Pendulum body
Inertia wheel
Active articulation
Passive articulation
Frame
How it works?
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 23
Control PC
Power supply (12V)
Motor driver
Inclinometer
Pendulum body
Inertia wheel Input/output card
Mechanical part Electric/electronic part
Micro strain FAS-G
Maxon EC-Powermax 30 (DC Brushless)
encoder
Experimental setup
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 24
Stabilization Control Problem
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 25
Control problem formulation
O O
Assume the system in some initial condition
Find a control input u to bring to and maintain it around this point
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 26
Proposed control solutions for stabilization
Linear state feedback control
LQR control
Predictive control (GPC, NMPC)
Passivity-based control
Sliding mode control & HOSMC
Flatness-based control
… etc
Nominal
Punctual disturbancePersistent disturbance
Punctual & persistent
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 27
Experimental results for Stabilization
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 28
Real-time experimental results for stabilization
Scenario 1 : Stabilization in the nominal caseIntroduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 29
Real-time experimental results for stabilization
Scenario 2 : Case with persistent disturbanceIntroduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 30
Real-time experimental results for stabilization
Scenario 3 : Case with punctual disturbance
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 31
Real-time experimental results
Scenario 4 : Combination of the two disturbances
0 5 10 15 20 25 30-5
0
5
10
Temps[s]
1[r
ad
]
La position angulaire du pendule inversé
0 5 10 15 20 25 30-6
-4
-2
0
2
4
6
temps[s]
d
1[r
ad
/s]
La vitesse angulaire du pendule inversé
0 5 10 15 20 25 30-500
0
500
1000
1500
2000
Temps[s]
d
2[r
ad
/s]
La vitesse angulaire du volant d'inertie
0 5 10 15 20 25 30-5
0
5
10
Temps[s]
U[N
m]
Le couple du volant d'inertie
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 32
Limit Cycles Generation Control Problem
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 33
Control problem formulation
O
Assume that the system in some initial condition
Find a control input u to bring and maintain it around an oscillating trajectory
While keeping the internal dynamics stable
O
Stable
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 34
Proposed control solutions for limit cycle generation
First solution : Trajectories optimization
Optimisation
Partial feedback Linearization
+ PID
Polynomial Reference Trajectories
System
Persistent disturbances
Estimation
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 35
Proposed control solutions for limit cycle generation
The reference trajectories are generated given a parameter p
These trajectories are tracked (on unactuated coordinate) by a first model-free controller
Parameter p is updated by the second model-free controller (stabilize actuated coordinate)
+-
Second solution : A dual model-free control scheme
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 36
Simulation and experimental results
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 37
Simulation & real-time experimental results
Conditions initiales
Cycle limite
First solution – Simulation – Nominal case
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 38
First solution – Experiment – Nominal case
Conditions initiales
Cycle limite
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 39
First solution – Simulation – Disturbance rejection
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 40
First solution – Experiment – Disturbance rejection
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 41
First solution – Simulation – Persistent disturbance
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 42
First solution – Experiment – Persistent disturbance
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 43
First solution – Experiment – Nominal Case + Disturbance Rejection
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 44
First solution – Experiment – Persistent Disturbance
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Simulation & real-time experimental results
Speaker : Ahmed CHEMORI 45
Conclusion
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
Speaker : Ahmed CHEMORI 46
Conclusion
Introduction
Context
Platform
Conclusion
Stabilization
Limit Cycle
• Control of underactuated mechanical systems• Those systems with less actuators than DOFs• Deal with two problems : Stabilization & Stable limit cycle generationP
rob
lem
Ch
alle
nge
sSo
luti
on
sV
alid
atio
ns
Deal with high nonlinear dynamics High coupling between actuated and unactuated DOFs Unstable internal dynamics Non minimum phase
Stabilization : Different control schemes (linear and nonlinear)
Limit cycle generation : Two control schemes (Trajectories optimization / Dual model-free)
Validation in simulation (different scenarios) Real-time experiments implementation on inertia wheel inverted pendulum Stable motions Robustness to external disturbances
Find more videos on Ahmed CHEMORI’s YouTube channel:
Robot Control
Email : [email protected]
www.lirmm.fr/~chemori/ Papers are available on
ResarchGate:
See more experimental videos on:
