Modeling, Analysis and Control of Mechanoreceptors with Adaptive Features

This work—the development of new control strategies and sensor models—is motivated by the open question which occurred during analysis of the functional morphology of vibrissal sensor systems. The reception of vibrations is a special sense of touch, important for many insects and vertebrates. The latter realize this reception by means of hair-shaped vibrissae, to acquire tactile information about their environments. The vibrissa receptors are in a permanent state of adaption to filter the perception of tactile stimuli. This behavior now may be mimicked by an artificial sensor system. The sensor system is modeled as a spring-mass-damper system with relative degree two and the system parameters are supposed to be unknown, due to the complexity of biological systems. Using a simple linear model of a sensory system adaptive controllers are considered which compensate unknown permanent ground excitations. The working principle of each controller (feedback law including adaptor) is shown in numerical simulations which prove that these controllers in fact work successfully and effectively. Moreover, practical implementation of these controllers to a demonstrator in form of an electrical oscillating circuit results in various successful experiments which confirm the theoretical results.