Jesse B. Hoagg

Learn More
Abstract— For nonlinear systems with measured-input nonlinearities, a subspace identification algorithm is used to identify the linear dynamics with the nonlinear mappings represented as a linear combination of basis functions. A selectiverefinement technique and a quasi-Newton optimization algorithm are used to iteratively improve the representation of the(More)
We present an adaptive controller that requires limited model information for stabilization, command following, and disturbance rejection for mult-input multi-output minimum-phase discrete-time systems. Specifically, the controller requires knowledge of the open-loop system’s relative degree as well as a bound on the first nonzero Markov parameter. Notably,(More)
I n the popular literature there is a certain fascination with the concept of zero [1]–[3]. While today the inconspicuous 0 is taken for granted, the situation was different in the distant past. For example, the Romans had no symbol for 0, a fact memorialized by the jump from 1 B.C. to 1 A.D., a convention instituted in 531 A.D. [4, p. 91]. In contrast, the(More)
This paper considers parameter-monotonic direct adaptive command following and disturbance rejection for single-input single-output minimum-phase linear time-invariant systems with knowledge of the sign of the high-frequency gain (first non-zero Markov parameter) and an upper bound on the magnitude of the high-frequency gain. We assume that the command and(More)
Systems characterized by light damping present a challenging control problem and thus an important system identification problem. Large lightly damped structures are particularly prominent within the aerospace community, specifically large flexible space structures. This class of structures includes satellites, membranes, and other gossamer structures [1].(More)
T HE objective of model reference adaptive control (MRAC) is to control an uncertain system so that it behaves like a given referencemodel in response to specified referencemodel commands. MRAC has been studied extensively for both continuous-time [1–8] and discrete-time systems [7–12]. In addition, MRAC has been extended to various classes of nonlinear(More)
In this paper we investigate the robustness of an extended version of retrospective cost adaptive control (RCAC), in which less modeling information is required than in prior versions of this method. RCAC is applicable to MIMO possibly nonminimum-phase (NMP) plants without the need to know the locations of the NMP zeros. The only required modeling(More)