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Outline
- Industrial Control - Evolution or Revolution?
- Yesterday - “Status Quo” - DCS/PLC Control Systems
- Today - “Latest” developments - Networked I/O
- Tomorrow - “Intelligent” I/O - Peer-to-peer “host-less” I/O
- Future - “Self-organizing” Systems - Intelligent Agent-based Systems
- Yesterday - Centralized Hierarchical control
- Today - Industrial Networks
- Same paradigm - centralized controls
- Fieldbus
- BACnet
- MAP
- Disadvantages of Current Controls
- Still largely Master-Slave architectures
- PLC represents the control intelligence
- DCS is the coordinating intelligence
- Rooted in the Past
- Deterministic algorithms
- I/O is still relatively “slave” intelligence
- Lots of different interface protocols
- Struggle for inter-operability
- Tomorrow is already here - Peer-to-peer I/O
- “Autonomous” - self-acting I/O
- Local intelligence (CPU and memory)
- Peer-to-peer communications
- No “Host” or Central Intelligence
- The “Ghost-Host”
- Central “supervisor” for configuration
- Network computers provide HMI(MMI
- What is the name for this new Constrol Science?
- Chaos Control ?
- Complexity Control ?
- Autonomous I/O Systems ?
- Peer-to-Peer Control Systems ?
- Today - Autonomous I/O
- Approaching “Intelligent Agents”
- Peer-to-peer interactive controls
- Algorithmic, rule-based controls
- Can be made “robust” with algorithms
- Fault-tolerance with redundancy
- Still relatively “deterministic”
- Programming rooted in past practice
- Intelligent, Distributed Control
- Networks of intelligent devices, called nodes, that communicate using a common protocol
- Each node contains embedded intelligence that implements the protocol and performs the node's algorithmic control functions
- Each node includes a media interface which couples the node's processing resources with the communications media
- Peer-to-peer communication capability that does not require intervention by a master controller
- “Holonic Fractal Manufacturing based on autonomous,
multi-purpose, modular and re-configurable production lines/cells
will allow production of many different products of any quantity”
- Odo Struger - Allen-Bradley
- Can intelligent systems become self-organizing?
The essential ingredients
- Re-programmability (by others) over the network
- Ability to change “behavior” (self-re-programming)
Based on external or internal stimuli/algorithms
-
Critical Complexity
- When does processing power become intelligence?
- When does connected intelligence become "self-organizing"?
- Non-deterministic behavious of self-organized control systems
- Can we make “control systems” self-organizing?
- If we “give up”on deterministic behavior, we’d have to insert the
equivalent of Asimov’s Laws of Robotics - Specifically
dis-allow certain harmful characteristics, or behaviors
- Pinto's Laws of Self-organizing Controls
Control Systems will :
- maximize benefits
- minimize waste, and
- prevent accidents or harmful effects
- Optimum Complexity - Chaitin Corollary
- The “task” of a self-organizing control system would be
to achieve control using the most-effective (shortest)
control-algorithm.
- Stuart Kaufman - Santa Fe /95
“Are there complex systems which cannot, in principle, be assembled
by an evolutionary process?”
Perhaps self-organizing control systems can “evolve” to levels
of control and emergent complexity far beyond anything imagined
by conventional “deterministic” control systems.
- Stuart Kaufman
- "When a system of simple inter-acting components reaches
a certain level of complexity or inter-connectedness,
it undergoes a dramatic transition, or phase change."
- Chris Langton
- A systems computational capability peaks in a narrow
regime between highly periodic and chaotic behavior.
- Who will make the revolutionary breakthrough?
- “I am convinced that the nations and people who master the
new sciences of complexity will become the economic, cultural
and political super-powers of the next century”
- Heinz Pagels - the Dreams of Reason ('87)
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