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Foreword The subject of control system synthesis, and in particular robust control, has had a long and rich history. Since the 1980s, the topic of robust control has been on a sound mathematical foundation. The principal aim of robust control is to ensure that the performance of a control system is satisfactory, or nearly optimal, even when the system to be(More)
— We present an observer for estimating position, velocity, attitude, and gyro bias, by using inertial measurements of accelerations and angular velocities, magnetometer measurements, and satellite-based measurements of position and (optionally) velocity. The design proceeds in two stages: in Stage I, an attitude and gyro bias estimator is designed based on(More)
It is known that a linear time-invariant system subject to \input saturation" can be globally asymptotically stabilized if it has no eigenvalues with positive real parts. It is also shown by Fuller 4] and Sussmann and Yang 12] that in general one must use nonlinear control laws and only some special cases can be handled by linear control laws. In this paper(More)
The purpose of this paper is to examine the problem of controlling a linear time-invariant system subject to input saturation in order to have its output track (or reject) a family of reference (or disturbance) signals produced by some external generator. It is shown that a semi-global framework for this problem is a natural one. Within this framework, a(More)
SUMMARY In this paper, we study control of a chain of integrators under actuator saturation and non-additive disturbances. We shall show that boundedness of the states can be ensured if the disturbances are matched and integral-bounded; misaligned and magnitude-bounded; or a combination of the two, using either a static or a dynamic low-gain state feedback.(More)
—We study decentralized controller design for stabilization and pole-placement, in a network of autonomous agents with double-in-tegrator internal dynamics and arbitrary observation topology. We show that a simple multi-lead-compensator architecture, in particular one in which each agent uses a derivative-approximation compensator with three memory(More)