Self-tuning run-time reconfigurable PID controller

Digital PID control algorithm is one of the most commonly used algorithms in the control systems area. This algorithm is very well known, it is simple, easily implementable in the computer control systems and most of all its operation is very predictable. Thus PID control has got well known impact on the control system behavior. However, in its simple form the controller have no reconfiguration support. In a case of the controlled system substantial changes (or the whole control environment, in the wider aspect, for example if the disturbances characteristics would change) it is not possible to make the PID controller robust enough. In this paper a new structure of digital PID controller is proposed, where the policy-based computing is used to equip the controller with the ability to adjust it's behavior according to the environmental changes. Application to the electro-oil evaporator which is a part of distillation installation is used to show the new controller structure in operation

Context-aware adaptation in DySCAS

DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met

Comparison of smoothing filters in analysis of EEG data for the medical diagnostics purposes

This paper covers a brief review of both the advantages and disadvantages of the implementation of various smoothing filters in the analysis of electroencephalography (EEG) data for the purpose of potential medical diagnostics. The EEG data are very prone to the occurrence of various internal and external artifacts and signal distortions. In this paper, three types of smoothing filters were compared: smooth filter, median filter and Savitzky-Golay filter. The authors of this paper compared those filters and proved their usefulness, as they made the analyzed data more legible for diagnostic purposes. The obtained results were promising, however, the studies on finding perfect filtering methods are still in progress.Web of Science203art. no. 80

Smart network anomaly detection software architecture for network-enabled ubiquitous devices

In this paper we present an architecture for run-time reconfiguration of network-enabled ubiquitous devices. The whole idea is based on a policy-based system where the whole decision-making (e.g. anomaly detection-related) logic is provided in a form of an externally loaded policy file. The architecture is verified through real-life implementation on an embedded system whose sensitivity can be easily modified should a need arise in run-time without affecting network device/segment (and thus potentially a number of network services) so that they continue working while the re-configuration process is triggered

Reconfigurable autonomic control systems (Rekonfigurowalne autonomiczne systemy sterowania)

In this paper a very relevant issue related to reconfigurable autonomic real-time control systems is undertaken. Designers of this kind of systems have to balance on the one side the ability of their operation with virtually no (or with minimum) human intervention, but on the other side, they have to implement a mechanism for easy and efficient reconfiguration in response to changing environmental conditions (context awareness). Although there are many techniques that may potentially be used to implement autonomic behaviour (such as Artifical Neural Networks, Fuzzy Logic, etc) actually only policy-based computing seems to give the system designers enough freedom when it comes to specification of how the system should behave in response to the environmental changes. This ease results from the fact, that each policy is written using a Policy Description Language (PDL) which can be optimized for the given problem area (various control systems applications, business applications, etc) As each PDL (for example AGILE PDL) offers besides a specific structure also a set of keywords strictly related to the problem domain, the system designers can easily express relations between context variables changes (these reflect the environment / context changes) and the requested changes to the system behaviour in a descriptive way. This is a very big advantage of policy-based computing over the alternative technologies. Policies themselves constitute the software component "logic" and because they (and thus thelogic itself) can easily be replaced with newer (more optimized) versions, then in the result the same software component may behave completely different under the same environmental conditions. Policy-based computing is the ideal candidate technology to support reconfiguration of autonomic systems as this technology is not resource hungry, so it may be sucessfully applied to the embedded systems domain

Architecture for hierarchical policy-supervised fault detection component / middleware

In this paper an idea of a layered, hierarchical policy-supervised diagnostic / fault detection component and middleware supporting humans` decision-making will be presented. This system will be based on Open Decision Point architecture and as such the system will offer an ease of reconfiguration via policies replacement in the decision making component. For the diagnostic / decision making support purposes AGILE policies will be used. In order to present practical implementation of the subject architecture, a proof of concept application to the distillation column is described. Selected simulation results are used to show advantages of the proposed approach

Time expenses analysis of discrete state observers computation

In this paper detailed analysis of discrete state observers from the point of view of potential time expenses required for the observer computation is presented. The aim of this article is to present, what is the influence of choice of observer parameters on computation time consumption. The attention is paid most of all on the analysis of the possibility of application of the control systems in a distributed version in the context of discrete state reconstruction. All of numerical tests are conducted in the LAM/MPI environment

Application of agile policies to the problem of features interaction prevention

In case of more complex systems quite a typical situation is that there is a number of autonomic services (managers) which are responsible for providing of some specific functionalities. If the services are delivered by various vendors a situation when some of the functionalities (features) will be provided by more than one of them is very likely. Some of the fonctionalities may be in conflict and the only way to prevent the conflicts is to equip the services (managers) with the capability of limiting their behaviour only to these areas which are confict free. In this paper an application of Agile policies to the problem of features interaction will be presented. It will be shown that Agile policies have some structural featues which make them ideal for features interaction prevention without any complex system-wide solution

Context-aware fuzzy control systems

In this paper an example of a hierarchical context-aware run-time reconfigurable control system is presented. The context-awareness is resulting from using policy-based computing as a technology allowing the control system to replace its decision making logic in run-time in response to changing environment conditions. The proposed solution allows system experts to specify policies (AGILE policies) used in the Supervision Layer for the purpose of making decisions regarding the most appropriate controller configuration and on the other side, they can specify policies (Fuzzy Logic policies) used in the Control Layer in order to generate control signals allowing to achieve specified control goals. Novelty of the proposed solutions lays in combination of two technologies, Open Decision Point technology originating from the Software Engineering domain Policy-based Computing that is originating from the Knowledge Engineering domain in application to non-linear control systems