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A Simple Distributed Method for Control over Wireless Networks. Authors : Miroslav Pajic , Shereyas Sundaram , George J. Pappas and Rahul Mangharam. Presented by: Raquel Guerreiro Machado. Important Concepts. Wireless Networked Control Systems Distributive
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A Simple Distributed Method for Control over Wireless Networks Authors: MiroslavPajic, ShereyasSundaram, George J. Pappas and Rahul Mangharam Presented by: Raquel Guerreiro Machado
Important Concepts • Wireless Networked Control Systems • Distributive • Wireless: dynamics can change operating point and physical dynamics of the closed loops system • Mean Square Stability • Wireless Control Network (WCN) • Network as controller • Increases robustness to link failure • Enables system compositionality and scalability
Control Systems Sensors CONTROLLER PLANT Actuators
Networked Control Systems Routing Routing Controllers Sensors Actuators
Wireless Control Networks • No centralized controller • Each node maintain a state • States stored in nodes are obtained through linear combination of its previous state and neighbors information • Sensors: Plant’s state information • Control nodes: Node’s state • Plant’s inputs are computed from the Control node states that are neighbors of the actuators
Wireless Control Networks • Plant’s update procedure: • Node’s update procedure: • Closed-loop system:
Robustness to link failures • More realistic system model • Link quality modeled as probability of dropping packets • Unreliable link modeled as memoryless, discrete, independent and identically distributed random process
Robustness to link failures • State update procedure
Robustness to link failures • State update procedure
Robustness to link failures • The Wireless Control Network: Synthesis and Robustness • A simple Distributed Method for Control over Wireless Networks
Robustness to link failures • Extract the maximal probability if message drops (pm) for which there exists a configuration that guarantees MSS
Robustness to node failures • Precompute different stabilizing configurations that correspond to all possible choices of k or fewer nodes failing • Each node Nkdifferent sets of weights for all neighbors • Should maintain d*Nkscalar weights, d = # of neighbors • Design WCN so if some nodes fail it remains stable • Stability condition: • So far, can deal with a single node failure
Scheduling Communication • Each node transmits exactly once per frame • Possible to schedule more than one node per time slot • Graph coloring techniques • di is the maximal degree of interference graph • Minimum of di time slots. • Communication schedule is static
Scheduling Communication • WCN task: (T,,,)
New control loops • Can add a new plant if: • Each node can transmit all of its P+1 states in a single communication packet • Possible to schedule calculation of the (P+1)st linear combination with no effect to the other P calculations • Communication budget (): # of unused bytes in ’s transmission packet. • Computation budget (=): time left for computation in a given node.
Industrial Application • Flows: • Reflux (L) • Boilup (V) • Distillate (D) • Bottom flow • Outputs: • - top composition • - bottom composition • - liquid levels in the condenser • - liquid levels in the reboiler
Experimental Platform • Firefly embedded wireless nodes. • Based on Atmel ATmega1281 8-bit microcontroller • Chipcon CC2420 IEEE 802.15.4 standard-compliant radio transciever • Linear iterative procedure implemented as a simple task on top of the nano-RK RTOS • Period of WCN task is 80ms • The plant was implemented in Simulink • For the interface between Simulink and real hardware: National Instruments PCI-6229
Limitations and Future Work • WCN robustness to link failures analysis assume independent link failures. • Scheme to handle node failures can be applied only if the network topology the requirements for which there exists a stabilizing configuration • Assumes the topology of the WCM is specified a priori