scholarly journals Artificial Immune Systems: An Overview for Faulting Actuators

Actuators ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 53
Author(s):  
Kidd
Keyword(s):  
Real Time ◽  
Artificial Immune Systems ◽  
Adaptive Algorithms ◽  
Actuator Faults ◽  
Artificial Immune ◽  
Immune Systems ◽  
Limited Success ◽  
Fault Compensation

This paper reviews Artificial Immune Systems (AIS) that can be implemented to compensate for actuators that are in a faulted state or operating abnormally. Eventually, all actuators will fail or wear out, and these actuator faults must be managed if a system is to operate safely. The AIS are adaptive algorithms which are inherently well-suited to these situations by treating these faults as infections that must be combated. However, the computational intensity of these algorithms has caused them to have limited success in real-time situations. With the advent of distributed and cloud-based computing these algorithms have begun to be feasible for diagnosing faulted actuators and then generating compensating controllers in near-real-time. To encourage the application of AIS to these situations, this work presents research for the fundamental operating principles of AIS, their applications, and a brief case-study on their applicability to fault compensation by considering an overactuated rover with four independent drive wheels and independent front and rear steering.

Once More Unto the Breach

2011 ◽  
pp. 2151-2175
Author(s):  
Mark Neal ◽  
Jon Timmis
Keyword(s):  
Artificial Immune Systems ◽  
Endocrine System ◽  
The Self ◽  
Artificial Immune ◽  
Biologically Inspired ◽  
Immune Systems ◽  
Robot Controller ◽  
Computational Systems ◽  
And Robotics

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches in a biologically justifiable way. To this end we present a conceptual framework that integrates artificial neural networks, artificial immune systems and a novel artificial endocrine system. The natural counterparts of these three components are usually assumed to be the principal actors in maintaining homeostasis within biological systems. This chapter proposes a system that promises to capitalise on the self-organising properties of these artificial systems to yield artificially homeostatic systems. The components develop in a common environment and interact in ways that draw heavily on their biological counterparts for inspiration. A case study is presented, in which aspects of the nervous and endocrine systems are exploited to create a simple robot controller. Mechanisms for the moderation of system growth using an artificial immune system are also presented.

Artificial Immune Systems

2008 ◽  
pp. 150-179
Author(s):  
Darryl Charles ◽  
Colin Fyfe ◽  
Daniel Livingstone ◽  
Stephen McGlinchey
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Artificial Immune Systems ◽  
Effective Model ◽  
Simple Games ◽  
Artificial Immune ◽  
Immune Systems ◽  
Strategy Games ◽  
Rts Game

We now consider the problem of introducing more intelligence into the artificial intelligence’s responses in real-time strategy games (RTS). We discuss how the paradigm of artificial immune systems (AIS) gives us an effective model to improve the AI’s responses and demonstrate with simple games how the AIS work. We further discuss how the AIS paradigm enables us to extend current games in ways which make the game more sophisticated for both human and AI. In this chapter, we show how strategies may be dynamically created and utilised by an artificial intelligence in a real-time strategy (RTS) game. We develop as simple as possible RTS games in order to display the power of the method we use.

Once More Unto the Breach

2005 ◽  
pp. 340-366 ◽  
Author(s):  
Mark Neal ◽  
Jon Timmis
Keyword(s):  
Artificial Immune Systems ◽  
Endocrine System ◽  
The Self ◽  
Artificial Immune ◽  
Biologically Inspired ◽  
Immune Systems ◽  
Robot Controller ◽  
Computational Systems ◽  
And Robotics

The field of biologically inspired computing has generated many novel, interesting and useful computational systems. None of these systems alone is capable of approaching the level of behaviour for which the artificial intelligence and robotics communities strive. We suggest that it is now time to move on to integrating a number of these approaches in a biologically justifiable way. To this end we present a conceptual framework that integrates artificial neural networks, artificial immune systems and a novel artificial endocrine system. The natural counterparts of these three components are usually assumed to be the principal actors in maintaining homeostasis within biological systems. This chapter proposes a system that promises to capitalise on the self-organising properties of these artificial systems to yield artificially homeostatic systems. The components develop in a common environment and interact in ways that draw heavily on their biological counterparts for inspiration. A case study is presented, in which aspects of the nervous and endocrine systems are exploited to create a simple robot controller. Mechanisms for the moderation of system growth using an artificial immune system are also presented.

Developing an Algorithm for the Application of Bayesian Method to Software Using Artificial Immune Systems

2021 ◽  
Author(s):  
Shafagat Mahmudova
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Bayesian Method ◽  
Artificial Immune Systems ◽  
Artificial Immune ◽  
Computational System ◽  
Malicious Software ◽  
Immune Systems ◽  
Advantages And Disadvantages ◽  
Protection Systems

Abstract This study provides information on artificial immune systems. The artificial immune system is an adaptive computational system that uses models, principles, mechanisms and functions to describe and solve the problems in theoretical immunology. Its application in various fields of science is explored. The theory of natural immune systems and the key features and algorithms of artificial immune system are analyzed. The advantages and disadvantages of protection systems based on artificial immune systems are shown. The methods for malicious software detection are studied. Some works in the field of artificial immune systems are analyzed, and the problems to be solved are identified. A new algorithm is developed for the application of Bayesian method in software using artificial immune systems, and experiments are implemented. The results of the experiment are estimated to be good. The advantages and disadvantages of AIS were shown. To eliminate the disadvantages, perfect AISs should be developed to enable the software more efficient and effective.

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