Universal laws and architecture: Foundations for Sustainable Infrastructure

1. Universal laws and architecture:Foundations for Sustainable Infrastructure John Doyle Control and Dynamical Systems, EE, BioE Caltech

2. Caltech smartgrid research • Motivation: • uncertainty + • large scale • Optimization and control • demand response • power flow (Javad Lavaei) • PIs: Low, Chandy, Wierman,...

3. Current control SCADA EMS global • centralized • state estimation • contingency analysis • optimal power flow • simulation • human in loop • decentralized • mechanical relay system local slow fast mainly centralized, open-looppreventive, slow timescale

4. scalable, decentralized, real-time feedback, sec-min timescale Our approach endpoint based scalable control SCADA EMS global • local algorithms • global perspective relay system local slow fast We have technologies to monitor/control 1000x faster not the fundamental theories and algorithms

5. Architectural transformation Power network will go through similar architectural transformation in the next couple decades that phone network has gone through ? Deregulation started Tesla: multi-phase AC Enron, blackouts 1888 1980-90s Both started as natural monopolies Both provided a single commodity Both grew rapidly through two WWs 2000s 1876 1980-90s Deregulation started Bell: telephone Convergence to Internet 1969: DARPAnet

6. Architectural transformation ... to become more interactive, more distributed, more open, more autonomous, and with greater user participation ... while maintaining security & reliability

7. Caltech smartgrid research • Motivation: • uncertainty + • large scale • Optimization and control • demand response • power flow (Javad Lavaei) • PIs: Low, Chandy, Wierman,...

8. Proceedings of the IEEE, Jan 2007 OR optimization Fundamentals! What’s next? A rant Chang, Low, Calderbank, Doyle

9. “Universal laws and architectures?” Fundamentals! • Universal “conservation laws” (constraints) • Universal architectures (constraints that deconstrain) • Mention recent papers* • Focus on broader context not in papers • Lots of theorems • Lots of case studies * *try to get you to read them? Systems A rant

10. my case studies Fundamentals! • Networking and “clean slate” architectures • wireless end systems • info or content centric application layer • integrate routing, control, scheduling, coding, caching • control of cyber-physical • PC, OS, VLSI, antennas, etc (IT components) • Lots from cell biology • glycolytic oscillations for hard limits • bacterial layering for architecture • Neuroscience • Smartgrid, cyber-phys • Wildfire ecology • Medical physiology • Earthquakes • Lots of aerospace • Physics: turbulence, stat mech (QM?) • “Toy”: Lego, clothing, buildings, …

11. Requirements on systems and architectures dependable deployable discoverable distributable durable effective efficient evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simplicity stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable

12. Simplified, minimal requirements dependable deployable discoverable distributable durable effective efficient evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable robust safety scalable seamless self-sustainable serviceable supportable securable simple stable standards compliant survivable sustainable tailorable testable timely traceable ubiquitous understandable upgradable usable accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable

13. Requirements on systems and architectures dependable deployable discoverable distributable durable effective evolvable extensible failure transparent fault-tolerant fidelity flexible inspectable installable Integrity interchangeable interoperable learnable maintainable manageable mobile modifiable modular nomadic operable orthogonality portable precision predictable producible provable recoverable relevant reliable repeatable reproducible resilient responsive reusable safety scalable seamless self-sustainable serviceable supportable securable stable standards compliant survivable tailorable testable timely traceable ubiquitous understandable upgradable usable accessible accountable accurate adaptable administrable affordable auditable autonomy available credible process capable compatible composable configurable correctness customizable debugable degradable determinable demonstrable efficient simple sustainable robust

14. Requirements on systems and architectures efficient simple sustainable robust

15. Requirements on systems and architectures efficient simple sustainable robust

16. Requirements on systems and architectures sustainable fragile robust simple wasteful efficient complex

17. What we want sustainable fragile robust simple wasteful efficient complex

18. What we get fragile robust simple wasteful efficient complex

19. What we get fragile robust simple wasteful efficient complex

20. Amory B. Lovins, Reinventing Fire

21. I’m interested in fire… Very accessible No math

22. Accessible ecology UG math

23. Wildfire ecosystem as ideal example • Cycles on years to decades timescale • Regime shifts: grass vs shrub vs tree • Fire= keystone “specie” • Metabolism: consumes vegetation • Doesn’t (co-)evolve • Simplifies co-evolution spirals and metabolisms • 4 ecosystems globally with convergent evo • So Cal, Australia, S Africa, E Mediterranean • Similar vegetation mix • Invasive species

24. Today 2050 efficient wasteful Physics

25. Future evolution of the “smart” grid? sustainable fragile robust simple wasteful efficient complex

26. This paper aims to bridge progress in neuroscience involving sophisticated quantitative analysis of behavior, including the use of robust control, with other relevant conceptual and theoretical frameworks from systems engineering, systems biology, and mathematics. Very accessible No math Doyle and Csete, Proc Nat AcadSci USA, online JULY 25 2011

27. IEEE TRANS ON SYSTEMS, MAN, AND CYBERNETICS, JULY 2010, Alderson and Doyle Very accessible No math

28. Want to understand the space of systems/architectures Case studies? fragile Strategies? Hard limits on robust efficiency? Architectures? Want robust and efficient systems and architectures robust efficient wasteful

29. Technology? fragile At best we get one robust efficient wasteful

30. ??? fragile Often neither robust efficient wasteful

31. ??? Bad architectures? fragile ? gap? Bad theory? ? robust efficient wasteful

32. Exponential improvement in efficiency F 100% 10% 1% .1% http://phe.rockefeller.edu/Daedalus/Elektron/

33. Solving all energy problems? When will lamps be 200% efficient? 100% Exponential improvement 10% 1% .1% Note: this is real data! http://phe.rockefeller.edu/Daedalus/Elektron/

34. When will lamps be 200% efficient? Oops… never. 50% 10% 1% .1% Note: need to plot it right. http://phe.rockefeller.edu/Daedalus/Elektron/

35. Control, OR Comms Kalman Pontryagin Shannon Bode Nash Theory? Deep, but fragmented, incoherent, incomplete Von Neumann Carnot Boltzmann Turing Godel Heisenberg Physics Einstein Compute

36. Control Comms Shannon Bode • Each theory one dimension • Tradeoffs across dimensions • Assume architectures a priori • Progress is encouraging, but… fragile? slow? ? wasteful? Carnot Boltzmann Turing Godel Heisenberg Physics Compute Einstein

37. 2.5d space of systems and architectures fragile complex simple robust wasteful efficient

38. Conservation “laws”? fragile Case studies Sharpen hard bounds Hard limit wasteful

39. UG biochem, math, control theory Chandra, Buzi, and Doyle Most important paper so far.

40. CSTR, yeast extracts Experiments K Nielsen, PG Sorensen, F Hynne, H-G Busse. Sustained oscillations in glycolysis: an experimental and theoretical study of chaotic and complex periodic behavior and of quenching of simple oscillations. BiophysChem72:49-62 (1998).

41. 4 “Standard” Simulation v=0.03 3 2 1 0 0 20 40 60 80 100 120 140 160 180 200 2 v=0.1 1.5 1 0.5 0 0 20 40 60 80 100 120 140 160 180 200 1 v=0.2 0.8 0.6 0.4 0.2 0 20 40 60 80 100 120 140 160 180 200 Figure S4. Simulation of two state model (S7.1) qualitatively recapitulates experimental observation from CSTR studies [5] and [12]. As the flow of material in/out of the system is increased, the system enters a limit cycle and then stabilizes again. For this simulation, we take q=a=Vm=1, k=0.2, g=1, u=0.01, h=2.5.

42. 4 Experiments Simulation v=0.03 3 Why? 2 1 0 0 20 40 60 80 100 120 140 160 180 200 2 v=0.1 1.5 1 0.5 0 0 20 40 60 80 100 120 140 160 180 200 1 v=0.2 0.8 0.6 0.4 0.2 0 20 40 60 80 100 120 140 160 180 200 Figure S4. Simulation of two state model (S7.1) qualitatively recapitulates experimental observation from CSTR studies [5] and [12]. As the flow of material in/out of the system is increased, the system enters a limit cycle and then stabilizes again. For this simulation, we take q=a=Vm=1, k=0.2, g=1, u=0.01, h=2.5.

43. Glycolytic “circuit” and oscillations • Most studied, persistent mystery in cell dynamics • End of an old story (why oscillations) • side effect of hard robustness/efficiency tradeoffs • no purpose per se • just needed a theorem • Beginning of a new one • robustness/efficiency tradeoffs • complexity and architecture • need more theorems and applications Fundamentals!

44. autocatalytic? a? PFK? fragile? h? y? x? control? g? Robust =maintain energy charge w/fluctuating cell demand Rest? PK? rate k? robust? Tradeoffs? efficient? wasteful? Hard limit? Efficient=minimize metabolic overhead

45. Theorem! Fragility simple enzyme complex enzyme Metabolic Overhead

46. Fragility hard limits • General • Rigorous • First principle simple complex ? Overhead, waste • Domain specific • Ad hoc • Phenomenological Plugging in domain details

47. Control Wiener Comms Bode Shannon robust control Kalman • Fundamental multiscale physics • Foundations, origins of • noise • dissipation • amplification • catalysis • General • Rigorous • First principle ? Carnot Boltzmann Heisenberg Physics

48. Control Comms Wildly “successful” Complex networks Compute “New sciences” of complexity and networks edge of chaos, self-organized criticality, scale-free,… Stat physics Carnot Boltzmann Heisenberg Physics

49. Popular but wrong

50. Alderson &Doyle, Contrasting Views of Complexity and Their Implications for Network-Centric Infrastructure, IEEE TRANS ON SMC, JULY 2010 Control Comms Complex networks Compute doesn’t work Stat physics “New sciences” of complexity and networks edge of chaos, self-organized criticality, scale-free,… Carnot Boltzmann Heisenberg Physics