Framework for Adaptive Controller Design Over Wireless Delay-Prone Communication Channels

Control over wireless channels promises to be a great enabler for an interconnected world. Historically, the “control engineering” and “wireless communications” domains were seen as separate, but with upcoming 5G networks, joint design of wireless control systems promises large gains in both the domains for a wide range of applications. By means of a typical industrial use case of the automated guided vehicles (AGVs), we present a methodology to analyze the latency requirements along with the wireless links from a controller to a plant (downlink) and from a plant to its controller (uplink). From the perspective of a Wireless Communications Engineer, we present a framework to analyze the basic properties of the resulting control cycle in order to derive feasible latency values that differ from the commonly found values in the communications literature. Also, we highlight an approach to derive the proportional-derivative (PD) controller parameters that yield the best control performance according to the integral of absolute error (IAE) criterion. At last, we present the idea of a cross-domain manager (CDM) that is able to translate (in real-time) the current network performance metrics to optimal controller gains.

[1]  Gerhard Fettweis,et al.  5G-Enabled Tactile Internet , 2016, IEEE Journal on Selected Areas in Communications.

[2]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[3]  Robin J. Evans,et al.  Feedback Control Under Data Rate Constraints: An Overview , 2007, Proceedings of the IEEE.

[4]  Henrik Klessig,et al.  Requirements and current solutions of wireless communication in industrial automation , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[5]  Linda Bushnell,et al.  Stability analysis of networked control systems , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[6]  Dragan Nesic,et al.  A unified approach to controller design for systems with quantization and time scheduling , 2007, 2007 46th IEEE Conference on Decision and Control.

[7]  Richard H. Middleton,et al.  Feedback stabilization over signal-to-noise ratio constrained channels , 2007, Proceedings of the 2004 American Control Conference.

[8]  Wei Zhang,et al.  Stability of networked control systems , 2001 .

[9]  Jan Lunze,et al.  Control theory of digitally networked dynamic systems , 2014 .

[10]  Frank Kozin,et al.  A survey of stability of stochastic systems , 1969, Autom..

[11]  Henning Trsek,et al.  Isochronous Wireless Network for Real-time Communication in Industrial Automation , 2016 .

[12]  Christoph Schönfelder Industrie 1.0 bis 3.0 , 2018 .

[13]  Y. Tipsuwan,et al.  Control methodologies in networked control systems , 2003 .

[14]  Gene F. Franklin,et al.  Digital Control Of Dynamic Systems 3rd Edition , 2014 .

[15]  João Pedro Hespanha,et al.  A Survey of Recent Results in Networked Control Systems , 2007, Proceedings of the IEEE.