The design of controllers and observers often relies on first order models of the system in question. These models are often obtained either through step-response tests, through on-line or off-line identification or through development of a mathematical model. When the system in question has unknown or uncertain parameters, the developed model also contains uncertainties and the controller/observer design may result in bad performance or even instability. In this paper we present a combined design of a controller and an observer for scalar linear time-invariant systems with unknown parameters. We combine a model reference adaptive controller, which does not require a model of the system, with a Luenberger observer which uses the desired closed-loop dynamics as its model. We show through Lyapunov theory and by application of Barbǎlat's lemma that all error states in the closed-loop system converge to zero and that all signals are bounded. CCS CONCEPTS • Computing methodologies → Control methods; Modeling and simulation; • Applied computing → Engineering;