access icon openaccess PDF-based tuning of stochastic optimal controller design for cyber-physical systems with uncertain delay dynamics

Uncertain dynamics in communication network, including random delays and packet losses make it difficult to guarantee stability of cyber-physical systems (CPSs). Many existing works consider the uncertainties of network channel with strong assumptions that network delay bounds and its distribution are known a priori and time-invariant. However, these assumptions could be invalidated in realistic CPSs by malicious attacks, system hardware faults, topology changes etc. A probability density function (PDF)-based tuning of stochastic optimal control (PTSOC) is proposed to manage the unknown dynamics in the embedded network. The update law of the proposed controller is derived and updated based on the PDF estimation of network delays that explicitly consider delays and its time-varying distribution. The results illustrate that the proposed PTSOC has a better performance in terms of the overshoot, convergence time, and cost when compared with the conventional stochastic optimal control.

Inspec keywords: stability; delays; control system synthesis; time-varying systems; cyber-physical systems; convergence; stochastic systems; optimal control; uncertain systems; probability

Other keywords: packet losses; uncertain delay dynamics; cyber-physical systems; PTSOC; time-varying distribution; probability density function based tuning; PDF-based tuning; network delay bounds; convergence time; system hardware faults; embedded network; network channel uncertainties; communication network; CPS; random delays; network delays; PDF estimation; stochastic optimal controller design; malicious attacks

Subjects: Stability in control theory; Optimal control; Control system analysis and synthesis methods; Distributed parameter control systems; Other topics in statistics; Time-varying control systems

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http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cps.2016.0012
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