ABSTRACT
The design of autopilots for high-performance aircraft was one of the primary motivations for active research in adaptive control in the early 1950s. Aircrafts operate over a wide range of speeds and altitudes, and their dynamics are nonlinear and conceptually time-varying. For a given operating point, specified by the aircraft speed (Mach number) and altitude, the longitudinal nonlinear aircraft dynamics can be approximated by a linear model. As the aircraft goes through different flight conditions, the operating point changes. These changes cannot be handled by constant gain feedback control. Since the output response y(t) carries information about the state as well as the parameters, onemay argue that in principle, a sophisticated feedback controller should be able to learn about the plant changes by processing the input/output (I/O) measurements (u, y) and choosing the appropriate controller from a list or design a new one in real-time. The real-time or on-the-fly selection or design of the controller is what distinguishes adaptive from nonadaptive schemes. Figure 35.1 illustrates this general adaptive control structure. The structure covers almost all classes of adaptive control. The idea is to process the I/O and possibly auxiliary measurements and decidewhat controller to use in real-time.Under this generic structure one can include gain scheduling where the real time controller design block is just a look-up table with a scheduler logic. In identifier-based schemes, this block includes a parameter estimator and the online calculation of the controller whereas in nonidentifier-based schemes, the block may consist of multiple models, stored controllers, and so on and an appropriate logic for selecting the right controller in real-time. Structures such as direct and indirect adaptive control also fall into this general feedback structure.
