Microgas turbine (MGT) engines in the range of 1–100 kW are playing a key role in distributed generation applications, due to the high reliability and quick load following that favor their integration with intermittent renewable sources. Micro-combined heat and power (CHP) systems based on gas turbine technology are obtaining a higher share in the market and are aiming at reducing the costs and increasing energy conversion efficiency. An effective control of system operating parameters during the whole engine lifetime is essential to maintain desired performance and at the same time guarantee safe operations. Because of the necessity to reduce the costs, fewer sensors are usually available than in standard industrial gas turbines, limiting the choice of control parameters. This aspect is aggravated by engine aging and deterioration phenomena that change operating performance from the expected one. In this situation, a control architecture designed for healthy operations may not be adequate anymore, because the relationship between measured parameters and unmeasured variables (e.g., turbine inlet temperature (TIT) or efficiency) varies depending on the level of engine deterioration. In this work, an adaptive control scheme is proposed to compensate the effects of engine degradation over the lifetime. Component degradation level is monitored by a diagnostic tool that estimates performance variations from the available measurements; then, the information on the gas turbine health condition is used by an observer-based model predictive controller to maintain the machine in a safe range of operation and limit the reduction in system efficiency.