Active noise control by an immune algorithm: adaptation in immune system as an evolution

A new information processing architecture is extracted from immune systems. By focusing on informational features of the immune system (i.e. specificity, diversity, tolerance, and memory), an immune algorithm is proposed. The algorithm proceeds in three steps: diversity generation, establishment of self-tolerance, and memorizing non-self. An agent-based architecture based on the local memory hypothesis and a network-based architecture based on the network hypothesis are discussed. An agent-based architecture is elaborated with an application to control systems where the knowledge about disturbances is not available. An adaptive disturbance neutralizer is formalized and simulated for a simple plant.