A Sequential Control Language for Industrial Automation

Current market trends for industrial automation are the need for customizable production, shorter time to market, and powerful global competitive pressure. Based on these trends two challenges have been identified: 1) flexible production systems and 2) integration and utilization of devices and software. Applications from both process automation, manufacturing, and robotics have been considered. More flexible languages and tools are needed to get a flexible production system. The graphical programming language Grafchart, based on the IEC 61131-3 standard language Sequential Function Charts (SFC), is considered with the aim to make both the language and its implementation more flexible. In particular, new constructs have been added to the Grafchart language and modern compiler techniques are evaluated for JGrafchart, a Grafchart implementation, with focus on an extensible language implementation. A first step toward real-time execution of Grafchart applications is also taken to make it possible to use Grafchart for hard real-time control. High execution rates often reveal concurrency issues and thus execution concurrency has also been investigated. Access to more data from industrial devices and software can be used to optimize production. Architectures for factory integration have been considered as this is the foundation to connect all devices and thus address the challenge of integrating and utilizing devices and software. Service Oriented Architecture (SOA) is a flexible software design methodology widely used in IT systems and for business processes. SOA service orchestration is brought to industrial automation by integrating support for both Devices Profile for Web Services (DPWS) and OPC Unified Architecture (OPC UA) in JGrafchart. Looking further, SOA 2.0 is event driven and features extremely loose coupling between components. An architecture based on SOA 2.0 where it is easy to integrate any device or software, in particular legacy devices with limited knowledge and capabilities, has been developed with focus on service choreography in industrial manufacturing. Another step toward real-time execution of Grafchart applications is integrated support for the high performance communication protocol LabComm. Additionally, it is investigated how Grafchart can be connected to Functional Mock-up Interface (FMI) for co-simulation to further address the shorter time to market trend by introducing simulation support. The PID controller is the most common controller for industrial automation. A PID implementation has been added to a Grafchart library and a flaw with the PID algorithm has been discovered. The problem occurs for PID controllers with a derivative part when the process value saturates. The derivative part then backs off which leads to undesired changes in the control signal. This issue has been analyzed and a solution to the problem is proposed

Implementation of an Autotunable Decoupling TITO Controller

In the process industry general TITO systems, i.e. systems with two inputs and two outputs, are usually assumed to be two separate systems. If the system is strongly coupled, the performance is generally poor, but usually nothing is done about this since there are no automatic means to improve it. The aim of this master's thesis is to develop a module with a completely automated design procedure which improves the performance of coupled TITO systems. For this to be possible an automated TITO system identification will be required, as well as automated decouple filter design and PID tuning for decoupled systems. Finally, to confirm that the developed module really works it is tested on a real process

An Interactive PID Learning Module for Educational Purposes

The PID controller is the most common controller and it is taught in most introductory automatic control courses. To develop an intuitive understanding of the basic concepts of the PID controller and PID parameter tuning, interactive and freely available tools are important. A PID module for educational purposes has been implemented in JGrafchart, a freely available development environment for the graphical programming language Grafchart. JGrafchart includes interactive graphical elements such as live plots and it is possibile to create animated graphics, for example of a simulated process. JGrafchart's variables, for example controller parameters and modes, can be changed interactively while executing. The PID module will be included in future releases of JGrafchart with sample applications which can be used for example to demonstrate a PID controller live in lectures or to let students interactively change controller parameters and modes to develop an intuitive understanding of the PID controller and PID parameter tuning. The sample applications are designed for users without any knowledge about JGrafchart and can be used to control both simulated and physical processes

Polymorphism for State Machines

In production industry today a lot of engineering time is required to develop and maintain control applications. One part of the control applications are the state machines which typically are written in Grafcet/SFC. Several efforts have been made to extend Grafcet/SFC to achieve more effective and convenient development, e.g. by introducing hierarchical structuring, reusable sub-state machines, and various means for convenient exception handling. Working with these extensions available also result in more maintainable and overviewable applications. The extensions are included in the Grafchart language, developed at Lund University, and have proved to both work and scale well for real applications. Extensions to support object orientated state machines have also been proposed and evaluated with good results, e.g. for batch applications. To improve reusability and to facilitate abstract modeling, complete polymorphism similar to that of ordinary textual object oriented languages such as Java or C++ is proposed. As an example it is shown that this kind of modeling fits well for modeling, encapsulating, and using robot capabilities; it facilitates making a coordination sequence conveniently reusable for any robot with the required set of capabilities and it also makes the capabilities themselves reusable for other coordination sequences. The intention is to include polymorphism in future versions of the freely available Grafchart tool JGrafchart, enabling you to easily evaluate the advantages of polymorphic state machines for your specific domain

Towards a seamless integration between process modeling descriptions at Business and Production levels - work in progress

To fulfill increasing requirements in the manufacturing sector, companies are faced with several challenges. Three major challenges have been identified regarding time-to-market, vertical feedback loops and level of automation. Grafchart, a graphical language aimed for supervisory control applications, can be used from the process-planning phase, through the implementation phase and all the way to the phase for execution of the process control logics, on the lower levels of the Automation triangle. Work in progress is examining if the same concepts could be used on the higher levels of the Automation triangle as well. By splitting the execution engine and the visualization engine of Grafchart various different visualization tools could potentially be used, however connected by the shared Grafchart semantics. Traditional Business languages, e.g. BPMN, could therefore continue to be used for the process-planning phase whereas traditional production languages, e.g. Grafchart or other SFC-like languages, could be used for the execution. Since they are connected through the semantics, advantages regarding the three identified challenges could be achieved; time-to-market could be reduced, the time delays in the vertical feedback loops could be reduced by allowing KPI visualization, and the level of automation could be increased

Service Orchestration with OPC UA in a Graphical Control Language

Production plants need to be set up and reconfigured faster to fulfill increasing market demands. Highly flexible automation systems are needed and a promising approach is Service Oriented Architecture (SOA) which has recently received much attention in both academia and industry. OPC Unified Architecture (OPC UA), the next generation of the de facto standard for interoperability in the automation domain, has SOA capabilities. In this paper it is presented how SOA service orchestration of OPC UA services can be done conveniently with a graphical control language. Generic support to use OPC UA servers has been integrated into the language and as an example it has been used to control a physical process which has been modeled, encapsulated, and exposed as an OPC UA server by wrapping it with an ethernet capable microcontroller

Next generation relay autotuners—analysis and implementation

In order to produce models for automatic controller tuning, this paper proposes a method that combines a short experiment with a novel scheme for approximating processes using low-order time-delayed models. The method produces models aimed to tune PI and PID controllers, but they could also be used for other model-dependent controllers like MPC. The proposed method has been evaluated in simulations on benchmark processes. It has also been implemented in an industrial controller and tested experimentally on a water-tank process. It is shown that our method is successful in estimating models for a variety of processes such as lag-dominated, delay-dominated, balanced, and integrating processes. We also demonstrate that the experiment time is both shorter and more predictable than currently used autotuners

Model optimization for autotuners in industrial control systems

Automatic tuning of PID controllers using relay feedback experiments has received attention on and off since it was first proposed and industrially implemented in a control system in the 1980s. While optimal experiment design and modern system identification easily outperform the original automatic tuner, they rely on computational resources that are not always available in industrial control systems. Here we present a combination of experiment and subsequent output-error identification of continuoustime first-order time-delayed (FOTD) system models, that requires very little in terms of computations and memory. The method has been extensively evaluated in simulation, and a prototype has been implemented for the ABB AC 800M controller family