European Control Conference 1993: Volume 1

adaptive algorithm analysis applied approach approximation assume assumption asymptotically bounded closed loop computation condition consider constant continuous convergence corresponding defined definite denote depends derived described determined discrete distributed disturbance dynamics equal equation error estimation example exists feedback Figure filter firing frequency function gain given holds identification IEEE initial input internal introduced kanban learning Lemma linear matrix means measurement method Mo pm neural network noise nonlinear Note observer obtained operator optimal output parameters performance plant poles polynomial positive possible presented problem procedure production Proof properties reference represents respect response robust satisfies shown shows signal simulation solution solved space stability stage step structure sufficient Th pm Theorem theory tion transfer function variables vector weights zero