Networked Control Applications Research Articles

PID controller tuning rules for integrating processes with varying time-delays

This paper discusses PID controller tuning for integrating processes with varying time-delays. Most of the existing tuning rules for the first-order lag plus integrator plus delay (FOLIPD) processes that we mainly focus on have the same general structure, and the properties of these rules are discussed in conjunction with varying time-delays. The analysis leads to novel tuning rules, where the maximum amplitude of an arbitrarily varying time-delay can be given as a parameter, which makes the use of the rules attractive in several applications. We will also extend the analysis to integrating processes with second-order lag and apply the design guidelines for a networked control application. In addition, we propose a novel tuning method that optimizes the closed-loop performance with respect to certain robustness constraints while also providing robustness to delay variance via jitter margin maximization. Further, we develop new PID controller tuning rules for a wide range of processes based on the proposed method. The new tuning rules are discussed in detail and compared with some of the recently published results. The work was originally motivated by the need for robust but simultaneously well-performing PID parameters in an agricultural machine case process. We also demonstrate the superiority of the proposed tuning rules in the case process.

Stability and Control of Systems with Uncertain Time-Varying Sampling Period and Time Delay

This paper addresses stability and control issues of systems with uncertain and time-varying sampling period and time-delay. These arise e.g. in embedded or networked control applications where limited computation or communication resources have to be scheduled. The uncertain and time-varying sampling period and time delay are transformed into polytopic and additive norm-bounded uncertainties in the discretized system description. Control design and stability analysis methods are given in the form of LMIs applying switched parameter-dependent quadratic Lyapunov functions. A reduction algorithm is proposed in order to decrease the amount of LMIs necessary for stability analysis. The control design and stability analysis methods as well as the reduction algorithm are illustrated by an example.

The Emergence of Industrial Control Networks for Manufacturing Control, Diagnostics, and Safety Data

The most notable trend in manufacturing over the past five years is probably the move towards networks at all levels. At lower levels in the factory infrastructure, networks provide higher reliability, visibility, and diagnosability, and enable capabilities such as distributed control, diagnostics, safety, and device interoperability. At higher levels, networks can leverage internet services to enable factory-wide automated scheduling, control, and diagnostics; improve data storage and visibility; and open the door to e-manufacturing. This paper explores current trends in the use of networks for distributed, multilevel control, diagnostics, and safety. Network performance characteristics such as delay, delay variability, and determinism are evaluated in the context of networked control applications. This paper also discusses future networking trends in each of these categories and describes the actual application of all three categories of networks on a reconfigurable factory testbed (RFT) at the University of Michigan. Control, diagnostics, and safety systems are all enabled in the RFT utilizing multitier networked technology including DeviceNet, PROFIBUS, OPC, wired and wireless Ethernet, and SafetyBUS p. This paper concludes with a discussion of trends in industrial networking, including the move to wireless for all categories, and the issues that must be addressed to realize these trends

Network centric approach to protection, control, and monitoring for power system

Due to the explosion in use of the Internet, it is expected that a variety of services will be provided through the communication network in the near future. Protection and control systems using the latest communication and information technology also allow for innovative solution to a wide range of power system problems. This paper describes a network-centric approach to protection, control, and monitoring systems. When the proposed “Network” devices, server, and browser can communicate with each other, they can share information which can enhance the overall protection and control of the power systems. The paper includes: overview of network devices, key technologies, protection and control applications, issues, and conclusion. © 2004 Wiley Periodicals, Inc. Electr Eng Jpn, 149(4): 31–41, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20006

Gain adaptation of networked dc motor controllers based on qos variations

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.

Distributed control applications within sensor networks

Sensor networks are gaining a central role in the research community. This paper addresses some of the issues arising from the use of sensor networks in control applications. Classical control theory proves to be insufficient in modeling distributed control problems where issues of communication delay, jitter, and time synchronization between components are not negligible. After discussing our hardware and software platform and our target application, we review useful models of computation and then suggest a mixed model for design, analysis, and synthesis of control algorithms within sensor networks. We present a hierarchical model composed of continuous time-trigger components at the low level and discrete event-triggered components at the high level.

Network Centric Approach to Protection, Control and Monitoring for Power Systems

Due to the explosion in use of the Internet, it is expected that a variety of services will be provided through the communication network in the near future. Protection and control systems using the latest communication and information technology also allow for innovative solution to a wide range of power system problems. This paper describes a network centric approach to protection, control and monitoring systems. When the proposed “Network” devices, server and browser can communicate with each other, they can share information which can enhance the overall protection and control of the power systems. The paper includes: overview of network devices, key technologies, protection and control applications, issues, conclusion.

Digital Gateways for Multimedia Home Networks

Residential networks are expected to open a huge market and introduce a bright, new era in telecommunications, by exponentially increasing the network usage, via broadband, added value services. Despite the business risks, investments made by the telecommunication industries clearly express the belief that the home networking market is about to take off. In this paper, a home network architecture for the provision of interactive multimedia services is considered and various access and indoor networking alternatives are presented. Then the focus is put on the Residential Gateway (RG), as a single point of networks convergence. Based on prototypes development, laboratory experiments and field trials throughout Europe and USA, a modular and a compact RG hardware architecture are described and compared, while the software architecture to support the RG functionality is described and the main building blocks are analyzed. Finally, a Web browser-based network management and control application that provides a visual metaphor of the RG is presented.

Hybrid fuzzy neural-network control for nonlinear motor-toggle servomechanism

This study addresses the application of a hybrid fuzzy neural network control (HFNNC) system to control a nonlinear mechanism system. First, the design procedures of the proposed HFNNC system are described in detail. In the HFNNC system, a fuzzy neural network (FNN) controller is the main tracking controller, which is used to mimic a perfect control law, and a compensated controller is proposed to compensate the difference between the perfect control law and the FNN controller. Then, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the FNN. Moreover, a toggle mechanism, which is driven by a permanent magnet (PM) synchronous motor, is studied as an example to demonstrate the effectiveness of the proposed control technique. The effectiveness of the proposed control scheme is verified by both the simulated and experimental results. In addition, the advantages of the proposed control system are indicated in comparison with the traditional computed torque control system.

Simulation Software Accelerates Development of Neural Network Control Applications in the Water Industry

Artificial neural network (ANN) applications have become popular in the field of water treatment process for modelling and control purposes. This is due to the fact that the processes are not well understood and also due to the large amounts of data available which are recorded for regulatory purposes. Development of such ANN applications are made more difficult by the data handling issues. It is often advantageous to try techniques developed on different plant data sets, under different operating conditions etc, but this is difficult to achieve efficiently in software. In this research, however, we have described several different applications of ANNs to demonstrate the significant results which may be achieved. But more importantly we have shown how the ANN application development, modification, comprehensive testing and benchmarking can be efficiently completed. To simplify the presentation, we have omitted a section on neural network architectures and learning processes since this is adequately covered in the paper by Renotte et al included as part of this Special Feature.

Application of neural network control to distillation and an experimental comparison with other advanced controllers

This paper experimentally demonstrates a novel approach for process control that uses neural networks for gain prediction within nonlinear, multivariable and constraint accommodation. This strategy is implemented on a lab-scale, nonideal, methanol-water distillation column for servo, regulatory and constrained control. Experimental results also demonstrate a Generic Model Controller using a neural network as the steady-state model inverse that was developed and simulated earlier [S. Ramchandran, R.R. Rhinehart, A very simple structure for neural network control of distillation, J. Proc. Cont. 52) (1995) 115–128]. A comparative study of these two neural network model-based controllers with other advanced controllers (e.g. Nonlinear Process-Model Based Control; Model Predictive Control using Dynamic Matrix Control, [DMC] ™; and an Advanced Classical Control) is also shown.

Application of artificial neural network and fuzzy control for fed-batch cultivation of recombinant Saccharomyces cerevisiae

A recombinant Saccharomyces cerevisiae expressing β-galactosidase under the control of the GAL10 promoter was constructed. The strain was used as a model to study fuzzy control with neural network, which served as state estimators for fed-batch cultivation of recombinant cells. To optimize the expression of β-galactosidase the effects of medium enrichment and induction on cell growth and expression were investigated. The activity of β-galactosidase was 2-fold higher in the presence compared with in the absence of yeast extract in the basal medium. Furthermore, the specific activity of β-galactosidase increased with increasing galactose concentration up to 30 g/ l. Two artificial neural networks (ANNs) were developed to estimate glucose and galactose concentrations using on-line measurements of ethanol and biomass concentrations, culture volume and the amount of carbon source fed to the fermentor. To improve productivity and product yield of β-galactosidase two multi-variable fuzzy controllers were used to control the glucose and galactose feed rates during the cell growth and production phases, respectively. Experimental data show that under fuzzy control with neural network estimators, the productivity was 2.7-fold higher than that in the case of exponential feeding, and 1.7-fold higher than that in the case of exponential feeding with feedback compensation using ethanol concentration.

A neural networks software for the control engineers

When using the popular back-propagation neural networks for control applications, the training part was found to be most prohibitive misfortune of the first time control engineers. This paper attempts to contribute towards the description of techniques on how to handle critical situations during training to achieve a faster and smooth learning curve. The feed forward neural network learning scheme and recurrent neural models were extensively studied and programmed in the LEarning COntrol SOftware (LECOSO) software. In this learning control software the art of training was reviewed and carefully implemented with critical user interactive facilities during learning. This software is very useful especially for control engineers who wish to spend little effort in the time consuming process of learning but rather concentrate on the stability and plant feedback compensation problems.

A Comparison of Two Neurocontroller Architectures

The use of neural networks in control applications has made rapid progress in recent years. In this article, two neurocontroller architectures: a the specialised learning, and b the emulator/controller are compared. Both architectures allow a neural network to learn the difficult task of balancing an inverted pendulum on a moving cart. Computer simulation results show that learning is quite rapid and both architectures take a small number of trials 15--25 for balancing the inverted pendulum.

The Relation Between Creative Management and Control Technology in Conflict Resolution

Development of this thesis has arisen from two prior Papers: Creative Management in Conflict Resolution in Total Enviroment. Proc. European Management and Cybernetics Research Institute, Vienna, April 1988, and Further Applied Studies in Creative Management of Potential Conflict at National and International Levels. Budapest, June 1988.These two Papers proposed and gave examples of conflict resolution achieved by the application to total management control networks and decision structures the following new principles - In addition to the present systems of Tele-supervisory controls andapplications using only power and resources as the control determinants, the following control determinants and creative methods to achieve conflict resolution and resultant steady state stability should be used in the total regimes of neural and external cybernetic network control systems and application methodologies. Control determinants. Additional inputs to cybernetic network to existing Power and Resources only on a Deterministal Basis. Integrity - Truth; Environment - Beauty; Moral Standards - Goodness. Control methodology and input decision making: Tele -supervisory - Space; Time Control - Time. In accord with A. N. Whitehead, Notions of Creative Mankind in the Environment of a space time continuum. Whilst these are broad concepts the high rate of modern information and Telecommunication systems makes their potential as man-system cybernetics network advantageously manipulable and creative. In the present state of the art, the most effective demonstration of the potential is from case studies analysed on the basis of these stated principles in relation to past successes of Creative Management with a target of making the methodology universally applicable with appropriate adaptation. Case studies will in this paper outline more fully illustration of the proposed cybernetic and systems engineering and technology so that further research development and application can follow.

Performance of an Integrated, General-Purpose Networked Data Acquisition System

This paper describes a general-purpose real-time software system developed for a broad range of networked data acquisition and process control applications. Performance of the software on DEC LSI-11 and VAX computers, Ethernet, and CAMAC is presented, including measuremnents of network transfer rates, data acquisition rates, and interrupt response times.

Practical Experiences in the Use of Advanced Network Applications at the Finnish National Control Centre

The data processing system ordered for the National Control Centre included a topology program and a state estimation function, in addition to SCADA-functions. The SCADA-functions were implemented in 1981 and the latest application introduced was the state estimation function in 1983. This paper examines experiences obtained in the specification, implementation and actual use of the network control applications. When making the specification much emphasis was placed on the presentation of real time network data in an easily viewable manner. An effort was made to avoid presenting unessential data to the Control Centre. This was done by making use of information processed by the topology program. To some extent we have had to go back to using conventional techniques, in order to guarantee the good performance of the system in emergency situations. So far, the estimator has been used only to complete real-time measurement data. Here, too, our experiences with the estimator have been good. It has helped the power system dispatcher to control exceptional situations and persons responsible for the data acquisition system to find bad data. Changes occur continuously in the power structure. These changes must be updated in the network model. Routine updating should take place quickly and effortlessly. The report describes the maintenance of input data required by applications, initial problems and the current situation. Finally we will examine future plans for using the estimator and for implementing security monitoring functions.

An investigation of acidic phospholipids of myelin using CM cellulose chromatography and high-performance liquid chromatography

In this work we consider the application of an adaptive neural network control for a class of single input single output non linear systems. The method uses a neural network system of Radial Basis Function (RBF) type to approximate the feedback linearization law and a fuzzy inference system of Mamdani type to estimate the control signal error between the ideal unknown control signal and the actual control signal. The rule base of the Mamdani fuzzy system is constructed using simple expert reasoning. The parameters of the (RBF) controller are adapted and changed using the gradient descent law based on the estimated control error. The simulation is carried out on a three tanks system with the objective of controlling the level of one tank. The simulation results show that the proposed RBF-Mamdani scheme performs successful and robust control in comparison to the results obtained using a PI controller.