Digital control of multiple discrete passive plants over networks

Abstract-Thermal control is critical for real-time systems as overheated processors can result in serious performance degradation or even system breakdown due to hardware throttling. The major challenges in thermal control for real-time systems are (i) the need to enforce both real-time and thermal constraints; (ii) uncertain system dynamics; and (iii) thermal sensor noise. Previous studies have resolved the first two, but the practical issue of sensor noise has not been properly addressed yet. In this paper, we introduce a novel thermal control algorithm that can appropriately handle thermal sensor noise. Our key observation is that even a small zero-mean sensor noise can induce a significant steady-state error between the target and the actual temperature of a processor. This steady-state error is contrary to our intuition that zero-mean sensor noise induces zero-mean fluctuations. We show that an intuitive attempt to resolve this unusual situation is not effective at all. By a rigorous approach, we analyze the underlying mechanism and quantify the noised-induced error in a closed form in terms of noise statistics and system parameters. Based on our analysis, we propose a simple and effective solution for eliminating the error and maintaining the desired processor temperature. Through extensive simulations, we show the advantages of our proposed algorithm, referred to as Thermal Control under Utilization Bound with Virtual Saturation (TCUB-VS).

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“…wI Ts 2 ) and b = 2−wI Ts 2+wI Ts [3], [6]. The constant K p , K i , and w I are control gains from continuous dynamics.…”

Section: Thermal Control System Modelmentioning

confidence: 99%

When thermal control meets sensor noise: analysis of noise-induced temperature error

Kim

Park

Eun

et al. 2015

21st IEEE Real-Time and Embedded Technology and Applications Symposium

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“…We refer to both IPES and ZOH devices as IPESH. We present a noncausal version of the IPESH which is based on the causal version of the IPESH presented in [16], [43,Definition 4] and earlier work in [12] and [44].…”

Section: Mapping Dt To Ct Controller Variablesmentioning

confidence: 99%

“…Note that the ordering of the IPESH is reversed from typical applications [12], [16], [43], [44] in which the IPES is located at the output of a CT system and the ZOH is located at the input to the CT system. In [43, Appendix E], we show that such traditional IPESH arrangements are indeed causal and can be used to synthesize passive DT single-input singleoutput (SISO) LTI filters.…”

Section: Mapping Dt To Ct Controller Variablesmentioning

confidence: 99%

Design of Networked Control Systems Using Passivity

Kottenstette

Hall

Koutsoukos

et al. 2013

IEEE Trans. Contr. Syst. Technol.

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“…The relationships between the continuoustime and discrete-time wave variables is determined by the multi-rate passive sampler (denoted PS : M T s ) and multirate passive hold (denoted PH : M T s ). These two elements are a combination of the passive sampler and passive hold blocks (which have been instrumental in showing how to interconnect digital controllers to continuous-time systems in order to achieve L m 2 -stability [2], [11]; see [12]- [15] for interconnecting continuous-time plants to continuous-time controllers over digital networks) and a discrete-time passive upsampler and passive downsampler [3]. At the interface to the digital controller is an inner product equivalent sample (IPES) and zero-order (ZOH) hold block y ct (t) = y s (j), t ∈ [jM T s , (j + 1)M T s ) [11] which are used for analysis in order to relate continuous-time control inputs r ct (t) and continuous-time control outputs y ct (t) to the continuous-time plant inputs r p (t) and outputs y p (t).…”

Section: Yp(s)mentioning

confidence: 99%

“…Our team has investigated the use of passivity for the design of Networked Control Systems (NCS) [1] in the presences of time-varying delays [2], [3]. This paper presents an important new step in the design of networked control systems as it applies to control of a conic-(dissipative) plant inside the sector [a, b] in which |a| < b, 0 < b ≤ ∞.…”

Section: Introductionmentioning

confidence: 99%

Multi-rate networked control of conic (dissipative) systems

Kottenstette

LeBlanc

Eyisi

et al. 2011

Proceedings of the 2011 American Control Conference

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Abstract-This paper presents a novel multi-rate digitalcontrol system which preserves stability while providing robustness to time-delay and data loss. In addition, this architecture allows for high-order anti-aliasing filters to be included which do not adversely affect system stability. Therefore, it allows for improved noise-rejection and system performance as compared to traditional digital control systems. It is shown that this framework, based on passivity-based networked control principles, can be used to control not only passive-(dissipative) systems (systems inside the sector [0, ∞]) but conic-(dissipative) systems which are inside the sector [a, b] We demonstrate the applicability of our result through the direct position control of a single-degree of freedom haptic paddle which is inside the sector [−τ, ∞] in which 0 < τ < ∞.

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Digital control of multiple discrete passive plants over networks

Abstract: Abstract-This paper provides a passivity based framework to synthesize l

Cited by 16 publications

References 23 publications

When thermal control meets sensor noise: analysis of noise-induced temperature error

When thermal control meets sensor noise: analysis of noise-induced temperature error

Design of Networked Control Systems Using Passivity

Multi-rate networked control of conic (dissipative) systems

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