1. Intelligent Control, Its evolution, Recent Technology on Robotics
M.Yamakita
Dept. of Mechanical and Control Systems Eng.
Tokyo Inst. Of Tech.
2019/2/23

2. Key Technology of Intelligent Control
1. Machine Learning
(Iterative Learning Control+ Q-Learning )
2. Physically Inspired Non-Linear Control
( Passivity Based (Adaptive ) Control)
3. Fuzzy Control : Stability Issue
4. Evolutional Algorithm
5. Hybrid System
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3. Hierarchical Intelligent Control
INTELLIGENCE
PRECISION
Organization
Level
Coordination
Execution
MOTION
COORDINATOR
VISION
COMMUNICATION
CONTROLLER
ACTUATORS
HARDWARE
NETWORK …
ORGANIZER
DISPACHER
PLANNING
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4. (PID etc.) Iterative Learning Control (ILC) r(t) y(t) C P t y,r
Coordination Level
Execution Level
(PID etc.)
Iterative
Learning
Control
(ILC)
r(t)
y(t) C P t
y,r
Error
If the same operation is repeated, can we reduce the error based on
the error of the previous
trial ?
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5. Structure of ILC
Plant
Learning
Filter
Memory - +
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6. Q-Learning Statistic Iterative Optimization Method
Learning of optimal sequence of actions
Q table S1 S2 S3 S4 a1 a2 a3
a2,a3
a1,a2,a3 a1 a2 a3 S1
Q(1,1) S2 S3 S4
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7. Learning Rule Action Section
Randomly select action j at state i by a probability
(T is artificial temperature)
Update of Q-Table aj
r(si,aj) is positive reward Si S’
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8. New Representation of Systems
State Space Represenation
Port-Controlled Hamiltonian System Representation
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9. Shift of Equilibrium State
Disturbance Attenuation
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10. Control Example Mechanical Equation Generator Electrical Dynamics
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11. 2019/2/23

12. 2019/2/23

13. Evolutional Computation (EC)
Optimization Method inspired by Gene Dynamics
Example：　Travel Salesman Problem A B C D E
Coding A B C D E ・ 1 2 3 4 5 A ○ B C D E B A C E D .
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14. Evolutional Operations (I)
Selection and Duplication n g1 g2 gn
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15. Evolutional Operations (II)
Permutation
Optimization Process
START
Coding
Evolutional
Operation
Mutation
Good
Gen ?
END
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16. Stability Issue of Fuzzy Control
Takagi-Sugeno Model
If x is M11 and x is M12 then .
If x is Mn1 and x is Mn2 then
Singleton Fuzzifier + Product Inference + Weighted Average Deffuzifier
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17. Sufficient Condition of Stability of TS Model
[Theorem]
If there exists a positive definite matrix P satisfying
then the TS mode is globally asymptotically stable.
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18. Proof of the Theorem
Let consider a following criterion function as a candidate of
Lyapunov function:
Time derivative of the function along the trajectory is given by
From the Lyapunov stability theorem, we have the conclusion.
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19. Hybrid System Roughly Speaking
Hybrid System = Automation + Differential/Difference Eq.
Controller
Plant
Actuator
Generator
Interface
Automaton
D/D System
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20. Formal Definition of a Hybrid System
Controller (Discrete Event System:DES)
Plant
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21. Generation of Event
State transition of controller is occurred immediately
when
is generated.
Detection of event
Generation of event
Generation of input
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22. Simple Example (Temperature Control)35 30
off on V
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23. References
Watkins eta.: Technical Note: Q-Learning, Machine Learning 8, pp. 279/292 (1992)
M.Yamakita and K.Furuta:
T.Shen eta. : Adaptive L2 Disturbance Attenuation of Hamiltonian Systems with Parametric Perturbation and Application to Power Systems, submitted to Asian Journal of Control (2000)
D.B.Fogel: Evolutionary Computation: A New Transactions, IEEE Trans. On Evolutionary Computation, 1-1, 1(1998)
S.S.Farinwata eta. Ed.:Fuzzy Control, Wiley (2000)
K.Hirota eta.: Soft-Computing as a Breakthrough, Vol.39, Mach 2000, J. of SICE (2000) (in Japanese)
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