Integrated Communication and Control Systems: Part III—Nonidentical Sensor and Controller Sampling

Networking in Integrated Communication and Control Systems (ICCS) introduces randomly varying delays which degrade the system dynamic performance and are a source of potential instability. In Part I [1] of this sequence of papers we developed a discrete-time, finite-dimensional model of the delayed control system for analysis and design of ICCS where the sensor and controller have identical sampling rates. In Part II [2] we proposed two alternative approaches for ICCS design, namely, identical and nonidentical sampling rates for sensor and controller. This Part III presents extended modeling of ICCS for nonidentical sensor and controller sampling rates. This model is also suitable for analyzing tracking problems, i.e., control systems with time-dependent reference inputs.

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Integrated Communication and Control Systems: Part II—Design Considerations

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3152699 ◽

1988 ◽

Vol 110 (4) ◽

pp. 374-381 ◽

Cited By ~ 161

Author(s):

Asok Ray ◽

Yoram Halevi

Keyword(s):

Control Systems ◽

Dynamic Performance ◽

Sufficient Conditions ◽

System Stability ◽

Time Varying ◽

Control Loops ◽

Analysis And Design ◽

Integrated Communication ◽

And Control ◽

Analytical Approaches

Asynchronous time-division multiplexed networks, used in Integrated Communication and Control Systems (ICCS), introduce time-varying and possibly stochastic delays in the feedback control loops. The objective of this on-going research is to develop a comprehensive methodology for the analysis and design of the above class of delayed control systems. In the first part [1] of this two-part paper, we developed a discrete-time, finite-dimensional, time-varying model of the delayed control system; necessary and sufficient conditions for system stability have been established for periodically varying delays. This second part elucidates the significance of the above model relative to the system dynamic performance as well as addresses major criteria for and outlines alternative analytical approaches to ICCS design. Pertinent concepts are illustrated by simulation.

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Integrated Communication and Control Systems: Part I—Analysis

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3152698 ◽

1988 ◽

Vol 110 (4) ◽

pp. 367-373 ◽

Cited By ~ 379

Author(s):

Yoram Halevi ◽

Asok Ray

Keyword(s):

Control System ◽

Control Systems ◽

Dynamic Performance ◽

Digital Data ◽

Time Varying ◽

Data Traffic ◽

Time Model ◽

Loop Control ◽

Integrated Communication ◽

And Control

Computer networking is a reliable and efficient means for communications between disparate and distributed components in complex dynamical processes like advanced aircraft, spacecraft, and autonomous manufacturing plants. The role of Integrated Communication and Control Systems (ICCS) is to coordinate and perform interrelated functions, ranging from real-time multi-loop control to information display and routine maintenance support. In ICCS, a feedback control loop is closed via the common communication channel which multiplexes digital data from the sensor to the controller and from the controller to the actuator along with the data traffic from other loops and management functions. Due to the asynchronous time-division multiplexing of the network protocol, time-varying and possibly stochastic delays are introduced in the control system, which degrade the system dynamic performance and are a source of potential instability. The paper is divided into two parts. In the first part, the delayed control system is represented by a finite-dimensional, time-varying, discrete-time model which is less complex than the existing continuous-time models for time-varying delays; this approach allows for simpler schemes for analysis and simulation of ICCS. The second part of the paper addresses ICCS design considerations and presents simulation results for certain operational scenarios of ICCS.

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Performance Analysis of Integrated Communication and Control System Networks

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2896153 ◽

1990 ◽

Vol 112 (3) ◽

pp. 365-371 ◽

Cited By ~ 13

Author(s):

Y. Halevi ◽

A. Ray

Keyword(s):

Control System ◽

Statistical Analysis ◽

Performance Analysis ◽

Control Systems ◽

Manufacturing Plants ◽

Asynchronous Time Division Multiplexing ◽

Processing Plants ◽

Integrated Communication ◽

Time Division ◽

And Control

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks [1–4] that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

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Dynamic performance and stability of integrated communication and control systems

10.2514/6.1987-2603 ◽

1987 ◽

Author(s):

ASOK RAY ◽

YORAM HALEVI ◽

LUEN-WOEI LIOU

Keyword(s):

Control Systems ◽

Dynamic Performance ◽

Integrated Communication ◽

And Control

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A Stochastic Regulator for Integrated Communication and Control Systems: Part I—Formulation of Control Law

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2896464 ◽

1991 ◽

Vol 113 (4) ◽

pp. 604-611 ◽

Cited By ~ 88

Author(s):

Luen-Woei Liou ◽

Asok Ray

Keyword(s):

Performance Evaluation ◽

Control Systems ◽

Dynamic Performance ◽

State Feedback Control ◽

Control Law ◽

Spatially Distributed ◽

Integrated Communication ◽

Finite Time Horizon ◽

And Performance ◽

And Control

Integrated Communication and Control Systems (ICCS), recently introduced and analyzed in a series of papers [1–7], are applicable to complex dynamical processes like advanced aircraft, spacecraft, automotive, and manufacturing processes. Time-division-multiplexed computer networks are employed in ICCS for exchange of information between spatially distributed plant components as well as for coordination of the diverse control and decision-making functions. Unfortunately, an ICCS network introduces randomly varying, distributed delays within the feedback loops in addition to the digital sampling and data processing delays. These network-induced delays degrade the system dynamic performance, and are a source of potential instability. This two-part paper presents the synthesis and performance evaluation of a stochastic optimal control law for ICCS. In this paper, which is the first of two parts, a state feedback control law for ICCS has been formulated by using the dynamic programming and optimality principle on a finite-time horizon. The control law is derived on the basis of a stochastic model of the plant which is augmented in state space to take into account the effects of randomly varying delays in the feedback loop. The second part [8] presents numerical analysis of the control law and its performance evaluation by simulation of the flight dynamic model of an advanced aircraft.

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On Modeling of Integrated Communication and Control Systems

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.2896212 ◽

1990 ◽

Vol 112 (4) ◽

pp. 790-794 ◽

Cited By ~ 2

Author(s):

Luen-Woei Liou ◽

Asok Ray

Keyword(s):

Communication Network ◽

Control System ◽

Control Systems ◽

Distributed Delays ◽

Asynchronous Time Division Multiplexing ◽

Integrated Communication ◽

Time Division ◽

And Control ◽

Relationship Of ◽

The Relationship

In a two-part paper [1,2], Ray and Halevi reported modeling of Integrated Communication and Control Systems (ICCS). Varying and distributed delays are introduced in the control system due to asynchronous time-division multiplexing in the communication network. This correspondence illustrates the relationship of Ray and Halevi’s approach to that of Kalman and Bertram [3] under nonsynchronous sampling.

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Robust Compensation of Distributed Delays in Integrated Communication and Control Systems

1991 American Control Conference ◽

10.23919/acc.1991.4791786 ◽

1991 ◽

Author(s):

Zhihong Zhang ◽

Asok Ray ◽

Hong Shen

Keyword(s):

Control Systems ◽

Distributed Delays ◽

Integrated Communication ◽

And Control ◽

Robust Compensation

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Development of a Ring Permeability Test System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.136.153 ◽

2010 ◽

Vol 136 ◽

pp. 153-157

Author(s):

Yu Hong Du ◽

Xiu Ming Jiang ◽

Xiu Ren Li

Keyword(s):

Control System ◽

Control Method ◽

Dynamic Performance ◽

Experimental Tests ◽

Measuring Method ◽

Test System ◽

Fluid Theory ◽

And Control ◽

Relationship Of ◽

The Mathematical Model

To solve the problem of detecting the permeability of the textile machinery, a dedicated test system has been developed based on the pressure difference measuring method. The established system has a number of advantages including simple, fast and accurate. The mathematical model of influencing factors for permeability is derived based on fluid theory, and the relationship of these parameters is achieved. Further investigations are directed towards the inherent characteristics of the control system. Based on the established model and measuring features, an information fusion based clustering control system is proposed to implement the measurement. Using this mechanical structure, a PID control system and a cluster control system have been developed. Simulation and experimental tests are carried out to examine the performance of the established system. It is noted that the clustering method has a high dynamic performance and control accuracy. This cluster fusion control method has been successfully utilized in powder metallurgy collar permeability testing.

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Multi-objective particle swarm optimisation approach for production-inventory control systems

Journal of Modelling in Management ◽

10.1108/jm2-02-2018-0027 ◽

2018 ◽

Vol 13 (4) ◽

pp. 1037-1056 ◽

Cited By ~ 2

Author(s):

Huthaifa AL-Khazraji ◽

Colin Cole ◽

William Guo

Keyword(s):

Control System ◽

Control Systems ◽

Inventory Control ◽

Dynamic Performance ◽

Particle Swarm ◽

Particle Swarm Optimisation ◽

Inventory Level ◽

Content Type ◽

Multi Objective ◽

Production Inventory

Purpose This paper aims to optimise the dynamic performance of production–inventory control systems in terms of minimisation variance ratio between the order rate and the consumption, and minimisation the integral of absolute error between the actual and the target level of inventory by incorporating the Pareto optimality into particle swarm optimisation (PSO). Design/method/approach The production–inventory control system is modelled and optimised via control theory and simulations. The dynamics of a production–inventory control system are modelled through continuous time differential equations and Laplace transformations. The simulation design is conducted by using the state–space model of the system. The results of multi-objective particle swarm optimisation (MOPSO) are compared with published results obtained from weighted genetic algorithm (WGA) optimisation. Findings The results obtained from the MOPSO optimisation process ensure that the performance is systematically better than the WGA in terms of reducing the order variability (bullwhip effect) and improving the inventory responsiveness (customer service level) under the same operational conditions. Research limitations/implications This research is limited to optimising the dynamics of a single product, single-retailer single-manufacturer process with zero desired inventory level. Originality/value PSO is widely used and popular in many industrial applications. This research shows a unique application of PSO in optimising the dynamic performance of production–inventory control systems.

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