Shared Communication Network Research Articles

A two-tier architecture for networked process control

Traditionally, process control systems utilize dedicated, point-to-point wired communication links using a small number of sensors and actuators to regulate appropriate process variables at desired values. While this paradigm to process control has been successful, chemical plant operation could substantially benefit from an efficient integration of the existing, point-to-point control networks (wired connections from each actuator/sensor to the control system using dedicated local area networks) with additional networked (wired or wireless) actuator/sensor devices. However, augmenting existing control networks with real-time wired/wireless sensor and actuator networks challenges many of the assumptions made in the development of traditional process control methods dealing with dynamical systems linked through ideal channels with flawless, continuous communication. In the context of control systems which utilize networked sensors and actuators, key issues that need to be carefully handled at the control system design level include data losses due to field interference and time delays due to network traffic. Motivated by the above technological advances and the lack of methods to design control systems that utilize hybrid communication networks, in the present work, we present a novel two-tier control architecture for networked process control problems that involve nonlinear processes and heterogeneous measurements consisting of continuous measurements and asynchronous, delayed measurements. This class of control problems arises naturally when nonlinear processes are controlled via control systems based on hybrid communication networks (i.e., point-to-point wired links integrated with networked wired/wireless communication) or utilizing multiple heterogeneous measurements (e.g., temperature measurements which can be taken to be continuous and species concentration measurements which are fed to the control system at asynchronous time instants and frequently involve delays). While point-to-point wired links are very reliable, the presence of a shared communication network in the closed-loop system introduces additional delays and data losses and these issues should be handled at the controller design level. In the two-tier control architecture presented in this work, a lower-tier control system, which relies on point-to-point communication and continuous measurements, is first designed to stabilize the closed-loop system, and an upper-tier networked control system is subsequently designed, using Lyapunov-based model predictive control theory, to profit from both the continuous and the asynchronous, delayed measurements as well as from additional networked control actuators to improve the closed-loop system performance. The proposed two-tier control architecture preserves the stability properties of the lower-tier controller while improving the closed-loop performance. The applicability and effectiveness of the proposed control method is demonstrated using two chemical process examples.

Quasi-decentralized model-based networked control of process systems

This paper develops a quasi-decentralized control framework for plants with distributed, interconnected units that exchange information over a shared communication network. In this architecture, each unit in the plant has a local control system that communicates with the plant supervisor – and with other local control systems – through a shared communication medium. The objective is to design an integrated control and communication strategy that ensures the desired closed-loop stability and performance for the plant while minimizing network utilization and communication costs. The idea is to reduce the exchange of information between the local control systems as much as possible without sacrificing stability of the individual units and the overall plant. To this end, dynamic models of the interconnected units are embedded in the local control system of each unit to provide it with an estimate of the evolution of its neighbors when measurements are not transmitted through the network. The use of a model to recreate the interactions of a given unit with one of its neighbors allows the sensor suite of the neighboring unit to send its data in a discrete fashion since the model can provide an approximation of the unit’s dynamics. The state of each model is then updated using the actual state of the corresponding unit provided by its sensors at discrete time instances to compensate for model uncertainty. By formulating the networked closed-loop plant as a hybrid system, an explicit characterization of the maximum allowable update period (i.e., minimum cross communication frequency) between each control system and the sensors of its neighboring units is obtained in terms of the degree of mismatch between the dynamics of the units and the models used to describe them. The developed control strategy is illustrated using a network of interconnected chemical reactors with recycle.

Integrated predictive control and scheduling co-design for networked control systems

A predictive control and scheduling co-design approach is proposed to deal with the controller and scheduler design for a set of networked control systems which are connected to a shared communication network. In the proposed approach, a predictive controller is applied to generate the control predictions for each system using delayed sensing data and previous control information, and a time delay compensator is designed at the actuator side to actively compensate for the network-induced delay in the forward channel when the control action is taken. Two different scheduling algorithms, the existing static rate monotonic (RM) scheduling algorithm and a new dynamic scheduling algorithm called dynamic feedback scheduling (DFS), are considered to schedule the transmissions of the control signals generated by the predictive controller, which are packed and transmitted to the actuator in one packet simultaneously. Both the scheduling algorithms are designed with the guarantee of the stability of all the systems, which is achieved by ensuring that the time delay of the systems do not exceed the upper bound under which the systems are stable. It is also pointed out that the RM algorithm is a special case of the proposed DFS algorithm, in the sense that the former can work only in a private network environment, whereas the latter extends its application to such networks where other components occupying the network. Simulations for both the RM and the DFS algorithms, illustrate the validity of the proposed approach.

A Survey of Recent Results in Networked Control Systems

Networked control systems (NCSs) are spatially distributed systems for which the communication between sensors, actuators, and controllers is supported by a shared communication network. We review several recent results on estimation, analysis, and controller synthesis for NCSs. The results surveyed address channel limitations in terms of packet-rates, sampling, network delay, and packet dropouts. The results are presented in a tutorial fashion, comparing alternative methodologies

STABILITY RESULTS FOR NETWORKED CONTROL SYSTEMS SUBJECT TO PACKET DROPOUTS

Stability and performance of networked control systems has been a recent area of interest in the control literature. The inclusion of a shared communication network between plant and controller inevitably leads to occasional random data loss. We provide novel results relating to the probability of such a system being globally asymptotically stable or input to state stable.

The influence of cultural similarity, type of relationship, and self‐monitoring on uncertainty reduction processes

This study examined the scope of Berger and Calabrese's (1975) uncertainty reduction theory of initial interactions in developed relationships. Multivariate analysis of covariance was employed to examine the influence of cultural similarity (intracultural vs. intercultural relationships), type of relationship (acquaintance vs. friend), and self‐monitoring (covariate) on self‐disclosure, interrogation, deception detection, attraction, attitude similarity, length of relationship, shared communication networks, and attributional confidence. Results indicated that each of the independent variables influenced the set of dependent variables and, as predicted, there was a significant interaction between cultural similarity and type of relationship. The findings suggest that selected aspects of the theory can be extended to culturally similar and dissimilar acquaintances and friendships. The present data identify boundary conditions (i.e., some theorems are limited in scope to the initial interaction context) for...