Controller and Scheduler Codesign for Feedback Control Over IEEE 802.15.4 Networks

Peters, Edwin G. W.; Quevedo, Daniel E.; Fu, Minyue

doi:10.1109/tcst.2016.2517571

Cited by 40 publications

(35 citation statements)

References 53 publications

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“…From the viewpoint of channel bandwidth utilization, several works have examined the stability and optimality issues in the codesign problem of NCS. By adopting an event‐triggered communication scheme, a codesign paradigm has been proposed in the works of Peng et al to simultaneously design an event‐triggered communication scheme and feedback controller that assure

{scriptH}_{\infty}

{scriptL}_{2}

performance of the NCS.…”

Section: Introductionmentioning

confidence: 99%

Optimal codesign of industrial networked control systems with state‐dependent correlated fading channels

Tamba

2019

Intl J Robust & Nonlinear

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Summary This paper examines a codesign problem in industrial networked control systems (NCS) whereby physical systems are controlled over wireless fading channels. The considered wireless channels are assumed to be stochastically dependent on the physical states of moving machineries in the industrial working space. In this paper, the moving machineries are modeled as Markov decision processes whereas the characteristics of the correlated fading channels are modeled as a binary random process whose probability measure depends on both the physical states of moving machineries and the transmission power of communication channels. Under such a state‐dependent fading channel model, sufficient conditions to ensure the stochastic safety of the NCS are first derived. Using the derived safety conditions, a codesign problem is then formulated as a constrained joint optimization problem that seeks for optimal control and transmission power policies which simultaneously minimize an infinite time cost on both communication resource and control effort. This paper shows that such optimal policies can be obtained in a computationally efficient manner using convex programming methods. Simulation results of an autonomous forklift truck and a networked DC motor system are presented to illustrate the advantage and efficacy of the proposed codesign framework for industrial NCS.

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{scriptH}_{\infty}

{scriptL}_{2}

performance of the NCS.…”

Section: Introductionmentioning

confidence: 99%

Optimal codesign of industrial networked control systems with state‐dependent correlated fading channels

Tamba

2019

Intl J Robust & Nonlinear

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“…Conductivity, density and permittivity of water are different from and higher than those of air [17], [18]. Water differs from the air, as it has higher conductivity, higher density and higher permittivity.…”

Section: Underwater Electromagnetic Wave Propagationmentioning

confidence: 95%

“…The average queue length, delay, and power consumption, at different number of hops for the proposed algorithm, have been evaluated and compared. Peters et al [18] have examined the influence of the scheduling policy on feedback control over networks based on a hybrid communication protocol, which incorporates both contention-free and contention-based medium access. A number of scheduler-controller co-design algorithms have been compared that take both the contention-based and guaranteed parts of the protocol into account using an approximation to an infinite horizon linear quadratic cost function.…”

Section: Related Workmentioning

confidence: 99%

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The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

Raina¹,

Jha²,

Bhattacharya³

2017

JTIT

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Abstract-Time synchronization between sensor nodes to reduce the end-to-end delay for critical and real time data monitoring can be achieved by cautiously monitoring the mobility of the mobile sink node in underwater wireless sensor networks. The Alive-in-Range Medium Access Control (AR-MAC) protocol monitors the delay of sensitive, critical and real-time data. The idea evolves as it involves reduction in duty cycle, precise time scheduling of active/sleep cycles of the sensors, monitoring the mobility of the sink node with the selection of appropriate queues and schedulers. The model for the path loss due to attenuation of electromagnetic wave propagation in the sea water is explained. The three-path reflection model evaluating reflection loss from the air-water and watersand interfaces as a function of distance between sensors and water depth is introduced. The algorithms for effective path determination and optimum throughput path determination are elaborated. The results verify that implementation of the Alive-in-Range MAC protocol has reduced the total number of packets dropped, the average queue length, the longest time in queue, the peak queue length and the average time in queue significantly, making it relevant for critical and real-time data monitoring.Keywords-Alive-in-Range MAC, effective path determination, mobile sink, optimum throughput path determination, underwater wireless sensor network.

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“…They also show that for linear single system problems with perfect communication it is computationally difficult to find optimal solutions. It must be noted that scheduling controller-actuator signals results in non-convex optimization problems, see Peters et al (2016).…”

Section: Introductionmentioning

confidence: 99%

Deep reinforcement learning for scheduling in large-scale networked control systems

2019

Self Cite

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This work considers the problem of control and resource scheduling in networked systems. We present DIRA, a Deep reinforcement learning based Iterative Resource Allocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards large-scale problems where control and scheduling need to act jointly to optimize performance. DIRA can be used to schedule general time-domain optimization based controllers. In the present work, we focus on control designs based on suitably adapted linear quadratic regulators. We apply our algorithm to networked systems with correlated fading communication channels. Our simulations show that DIRA scales well to large scheduling problems.

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Controller and Scheduler Codesign for Feedback Control Over IEEE 802.15.4 Networks

Cited by 40 publications

References 53 publications

Optimal codesign of industrial networked control systems with state‐dependent correlated fading channels

Optimal codesign of industrial networked control systems with state‐dependent correlated fading channels

The Alive-in-Range Medium Access Control Protocol to Optimize Queue Performance in Underwater Wireless Sensor Networks

Deep reinforcement learning for scheduling in large-scale networked control systems

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