Bertrand Russell is widely known for his willingness to change his philosophical mind. He is also now and again saddled with a reputation for carelessness about providing readers with clear and convincing explanations of his turnabouts. This chapter presents and briefly assesses the development of Russell's thinking about memory, emphasizing, against the grain of the received view, the continuity in his thought. Russell's ideas about memory are no exception to that perceived pattern of progress. The core notion of the early theory is that of acquaintance, by which Russell means a mode of cognition which is both immediate and purely receptive. The main ostensible problem for the theory is that of accounting for retention—specifically, making sense of the idea of being now acquainted with what has been and is no more. The abandonment of direct realism should predictably bring about a further increase in Russell's concern over fallibility and error in memory.

This paper considers the design and implementation of a discrete-time fast tracking controller for quadrotor vehicles subject to perturbations. The proposed controller consists of a model-based disturbance observer and a Composite Nonlinear Feedback (CNF) controller. The CNF control law introduces nonlinear damping to the system so that it possesses a fast rise time without overshoot. The least square identification method is applied to develop a model based disturbance observer, thus decoupling the problems of track following and disturbance rejection. Experimental results are provided in order to validate the proposed approach.

In this work a modified Resonant Controller is proposed to deal with the tracking/rejection problem of periodic signals robust to period variations and parametric uncertainties in the plant. The control strategy is based on a resonant structure in series with a notch filter, which will be responsible to improve the robustness to period variation. A robust state feedback controller is designed by solving a linear matrix inequality (LMI) optimization problem guaranteeing the robust stability of the closed loop system. A numerical example is presented to illustrate the method.