Evolutionary Design by Computers with CDrom
Evolutionary Design by Computers with CDrom
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Introduction to Multiagent Systems
Introduction to Multiagent Systems
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Immunocomputing: Principles and Applications
Immunocomputing: Principles and Applications
Immunity-Based Systems: A Design Perspective
Immunity-Based Systems: A Design Perspective
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The General Suppression Control Framework (GSCF) is a framework inspired by the suppression hypothesis of the immune discrimination theory. The framework consists of five distinct components, the Affinity Evaluator, Cell Differentiator, Cell Reactor, Suppression Modulator, and the Local Environment. These reactive components, each responsible for a specific function, can generate long-term and short-term influences to other components by the use of humoral and cellular signals. This paper focuses in the design of a control system that aims to balance and navigate a self-balancing robot though obstacles based on the five components in GSCF. The control system demonstrates how simple combination of suppression mechanism can filter and fuses two unstable measurements together to obtain reliable measurement to maintain the balance of a dynamically unstable system. The control system is implemented in a two-wheeled self-balancing robot for its inherited instability can best demonstrate the systems responsiveness to dynamic changes.