Research of Immune Controllers

2011 ◽  
pp. 262-303
Author(s):  
Fu Dongmei
Keyword(s):  
Control System ◽  
Immune System ◽  
B Cells ◽  
Control Systems ◽  
Artificial Immune System ◽  
General Structure ◽  
Engineering Application ◽  
Error Characteristic ◽  
Artificial Immune ◽  
The Stability

In engineering application, the characteristics of the control system are entirely determined by the system controller once the controlled object has been chosen. Improving the traditional controller or constructing the new controller is an unfading study field of control theory and application. The control system is greatly enriched and developed by this way. As a complicated self-adaptable system, the biological immune system can effectively and smoothly stand against antigens and viruses intruded into organism. It is possible to improve the self-learning, adaptive and robustness capability of the control system through embedded an artificial immune controller in control system. Based on the biological immune mechanism and artificial immune model, this chapter attempts to study the immune controller design and application in traditional control system..First, a kind of artificial immune controller is proposed based on the T-B cells immunity. The boundedness and the stability of SISO control systems, which constructed by the artificial immune controller, are proved by the little gain theorem. A general controller structure frame based on the T-B cells immunity is proposed, which includes the same kind of controller proposed previously. The validity of this artificial immune controller is verified by simulation. Second, a new type of artificial immune controllers is constructed according to a simple double-cell immune dynamics model. The non-error characteristic of SISO control systems, which constructed by the artificial immune controller, is proved by the nonlinear theory in this chapter. The I/O stability and no-error characteristic of the system are verified by simulations, which show that the kind of artificial immune system have good anti-lag capability. Third, the Varela immune network model has been improved based on which an artificial immune system is proposed. The odd linearization method of the non-linear system is used to prove the stability and non-error characteristic of the SISO system constructed by the artificial immune control system. Its I/O stability, non-error characteristic and strong anti-lag capability are also verified by simulation. Finally, based on the comparison of the three kinds of immune controllers, a general structure of the artificial immune controller is proposed. The further study on this field is indicated in this chapter lastly.

Effect of Reference Height Control System on CPG Networks for Quadruped Hopping Robot

2013 ◽  
Vol 313-314 ◽  
pp. 498-502
Author(s):  
A.M. Kassim ◽  
M.Z.A. Rashid ◽  
M.R. Yaacob ◽  
N. Abas ◽  
T. Yasuno
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Control Systems ◽  
Feedback Loop ◽  
Engineering Application ◽  
Pi Controller ◽  
Feedback Control System ◽  
Height Control ◽  
Hopping Robot ◽  
The Stability

In this paper, the collaboration of CPG networks with the feedback control system which are composed with the maximum hopping height detector and the Proportional Integral (PI) controller as an engineering application for the CPG network is proposed with the developed control systems. By adding the feedback loop through the feedback controller, the developed quadruped hopping robot not only can generate the continuous hopping performances but also can control the desired hopping height. As the result, the effectiveness of CPG networks to keep the stability of the developed quadruped hopping robot besides of confirming the validity of using reference height control system to generate hopping capability at different reference height, respectively.

The Role of Hypermutation and Affinity Maturation in AIS Approaches to Clustering

2015 ◽  
pp. 124-144
Author(s):  
Waseem Ahmad ◽  
Ajit Narayanan
Keyword(s):  
Immune System ◽  
B Cells ◽  
Unsupervised Learning ◽  
Similarity Measure ◽  
Artificial Immune System ◽  
Affinity Maturation ◽  
Artificial Immune ◽  
Basic Concepts

In recent years, several artificial immune system (AIS) approaches have been proposed for unsupervised learning. Generally, in these approaches antibodies (or B-cells) are considered as clusters and antigens are data samples or instances. Moreover, antigens are trapped through free-floating antibodies or immunoglobulins. In all these approaches, hypermutation plays an important role. Hypermutation is responsible for producing mutated copies of stimulated antibodies/B-cells to capture similar antigens with higher affinity (similarity) measure and responsible to create diverse pool of solutions. Humoral-Mediated Artificial Immune System (HAIS) is an example of such algorithms. However, there is currently little understanding about the effectiveness of hypermutation operator in AIS approaches. In this chapter, we investigate the role of the hypermutation operator as well as affinity threshold (AT) parameters in order to achieve efficient clustering solutions. We propose a three-step methodology to examine the importance of hypermutation and the AT parameters in AIS approaches to clustering using basic concepts of HAIS algorithm. Here, the role of hypermutation in under-fitting and over-fitting the data will be discussed in the context of measure of entropy.

Non-network Type Artificial Immune System and its Application to Automated Guided Vehicle (AGV) System

2000 ◽  
Vol 4 (1) ◽  
pp. 111-119
Author(s):  
Ben T. Nohara ◽  
◽  
Hiroko Takahashi ◽  
Keyword(s):  
Control System ◽  
Immune System ◽  
Artificial Immune System ◽  
Container Terminal ◽  
Automated Guided Vehicle ◽  
Artificial Immune ◽  
Restricted Area ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Network Type

This paper describes Artificial Immune-Based Control System that is applied to the automatic transportation control system of AGV (Automated Guided Vehicle) operated in a restricted area such as a container terminal and an ironworks. The authors propose the non-network type artificial immune system that is functioning in a unit level of antibodies instead of in a network of antigens and antibodies. AGVs equipped by the proposed method can avoid the collision and/or the deadlock and move autonomously from the source points to the destinations. The transportation system using AGVs has been expected because AGVs have the flexibility and efficiency. However the control system for AGVs is so flexible that the design has a big margin. Especially, the design for the control system is a hard work when the number of AGV becomes to be large. Only a few study of this problem is found in a past references. This paper focuses on the automatic transportation plan of AGVs in a real time scheduling using the non-network type artificial immune system. The comparison of the proposed method: the non-network type artificial immune system and the network type artificial immune system are also discussed and the computer simulation verifies the effectiveness of the proposed method.

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