Publications

This paper deals with the (adaptive) control of a sensory system. It is inspired by biological ideas concerning the behavior of animal receptor cells for the processing of information of the tactile sense. The equations of motion fall into the category of quadratic, finite-dimensional, nonlinearly perturbed, multi-input, multi-output systems (MIMO-systems) of relative degree two. Then, the typical adjustment of the receptor cells to continuing signals (described as perturbations from the environment) is realized via a universal adaptive control strategy, which also allows system parameter uncertainties, i.e., lack of precise knowledge. We present three control strategies, analytical proofs and simulations.

The paper presents an analytical method for derivation of the dynamic equations of motion of a continuous body with distributed parameters. So called reduced method is implemented to a worm motion in a tube. The method neglects less important degrees of freedom of the object. Final results of worm motion, as well as all necessary formulation and explanations are available.

This paper deals with the (adaptive) control of a sensory system, which is inspired by biological ideas concerning the behaviour of a tactile hair or sensillum. The cells for reception of vibrations adjust their sensibility to a continuing excitement, such that this permanent excitation of the whole system tends to the rest position. Hence, this biological paradigm demonstrates a fundamental principle: adaption. In general, one cannot expect to have complete information about a sophisticated mechanical or biological system, but instead only structural properties (e.g. minimum phase condition, strict relative degree) are known. Therefore, the method of adaptive control is chosen in this paper. The aim is to design a universal adaptive controller, which learns from the behaviour of the system, so automatically adjusts its parameters and achieves a pre-specified control objective. Since we deal with a nonlinearly perturbed multi-input, multi-output system, which is not necessarily autonomous, particular attention is paid to the lambda-tracking control objective. Simple adaptive servomechanisms, which achieve tracking of a given reference signal for any pre-specified accuracy (tracking-error) lambda, are introduced. We stress that the introduced adaptive controllers consist of very simple feedback mechanisms and adaptation rules. These controllers are only based on information about the output of the system - no knowledge of system parameters is required.