Towards a unified approach to detection of faults and cyber-attacks in industrial installations

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper investigates enhancing the ability to detect cyber-attacks by using information and methods related to fault detection. An experimental stand, and an associated simulator have been constructed to enable tests of combined cyber attacks and faults in industrial processes, and, possibly, to distinguish between them. Some scenarios of cyber attacks have been presented, analysed theoretically and then tested on the simulator, demonstrating that detection of cyber attacks by this method is possible.Peer ReviewedPostprint (author's final draft

COMPARISON OF OPTIMAL CONTROL STRATEGIES FOR SUPERVISORY AND REGULATORY LEVEL

Abstract: In this paper, the conditions for the equivalence between the supervisory level and regulatory level control strategies based on the same objective function are established. Both controllers use the same general objective function with constraints. It is shown that the supervisory controller modifies the control action of the fixed regulatory controller in such a way that the solution of general objective function with constraints is generated at the regulatory level. In order to demonstrate the theoretical results, the proposed controllers are applied to a power plant boiler simulator

Predictive control for industrial applications

An overview is first provided of some of the most common formulations of Predictive Control, such as Dynamic Matrix Control (DMC), Predictive Functional Control (PFC), Preview Control and Generalized Predictive Control (GPC). The main features, advantages and disadvantages are discussed. A new algorithm, based on a so called Linear Quadratic Generalized Predictive Controller (LQGPC) is then introduced. This algorithm combines features of Predictive Control with those of Linear Quadratic Gaussian Control, providing improved stability and robustness properties

Software tests for model based applications in the automotive industry

In automotive industry, computer control, fault detection and communication are becoming increasingly complex and interrelated with each other. This prompts development of formal methods for software design and verification. The model based development of automotive functionality has become extremely popular especially in drive train and engine applications. The approach appears to make the development more modular, with the programming code being more reusable and easier to test. This article looks at the advantages and disadvantages of this approach. It concerns the range of tests, from first component tests through integration and system tests to the final acceptance tests. It discusses model based development using the V model and shows some differences to code based development. The first component tests are generally divided into static tests (reviews, rule checkers, metrics, static analysis) and dynamic tests (model in the loop, software in the loop, processor in the loop). In addition, an important aspect is verification of models using non-floating point arithmetic, as this method of calculation of often used in automotive embedded computers (e.g. FPGA). The formal verification of such models is discussed. With respect to the integration tests, the article concentrates on some issues of hardware-in-the-loop testing. The system tests are also discussed, especially the structure of system information in a model based approach and the preconditions determined by hardware in the loop tests. In the final acceptance tests, the main problems contain: formal link between the system requirements and the test methods and coordination and optimisation of the whole test process. Current trends in automotive industry are toward higher level of integration of the development, verification and manufacturing of systems. Therefore, the traceability is also discussed, with a mention of a model of an integrated tool chain. The article shows the pit falls of tool orientation and a way out of the disaster. An example of software development and testing process in a leading automotive company will illustrate the considerations. Finally the article looks at the future of software development in automotive industry, will development of formal methods and increasing standardisation lead to a closer cooperation of different manufacturers