Abstract-This paper presents a sensor-based pedestrian tracking technology that does not rely on any infrastructure. The information about human walking is monitored by a sensor module composed of accelerometers, gyroscopes and magnetometers. The acquired information is used by an algorithm proposed in this paper to accurately compute the position of a pedestrian. Through the application of human kinetics, the algorithm integrates two traditional technologies: strap-down inertial navigation and pedestrian dead-reckoning. Based on the algorithm, this paper presents several methods to improve the accuracy of pedestrian tracking through reducing the integral drift which is the main cause of errors in inertial navigation. These methods have been carefully investigated through theoretical study, simulation and field experiment. The results indicate accurate tracking is achievable through the application of both the proposed algorithm and methods. Evidently, it is feasible to develop self-contained pedestrian tracking system using inertial/magnetic sensors, eliminating the need for complicated and normally expensive infrastructure that most existing tracking systems rely on.Index Terms-Human walking, inertial navigation system (INS), integral drift, pedestrian dead reckoning (PDR), pedestrian tracking, sensor module.
This paper presents a robust nonlinear H∞ output-feedback control approach for attitude manoeuvring of flexible spacecraft with external disturbances, inertia matrix perturbation and input constraints. By applying Lyapunov stability theory and using the generalized S-procedure and sum of squares (SOS) techniques, the robust H∞ output-feedback attitude control problem is converted into a convex optimization problem with SOS constraints when the flexible spacecraft is modelled as a polynomial state-space equation with polytope uncertainties. As a result, it overcomes the difficulty in constructing Lyapunov function and implementing numerical computation caused by the non-convexity of output-feedback H∞ control design for nonlinear systems. Moreover, it enables the state-observer and the controller to be designed independently and hence the complexity of the control algorithm is reduced remarkably. A numerical example illustrates the effectiveness and feasibility of the proposed approach.
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