This paper proposes new algorithms for attitude estimation and control based on fused inertial vector measurements using linear complementary filters principle. First, n-order direct and passive complementary filters combined with TRIAD algorithm are proposed to give attitude estimation solutions. These solutions which are efficient with respect to noise include the gyro bias estimation. Thereafter, the same principle of data fusion is used to address the problem of attitude tracking based on inertial vector measurements. Thus, instead of using noisy raw measurements in the control law a new solution of control that includes a linear-like complementary filter to deal with the noise is proposed. The stability analysis of the tracking error dynamics based on LaSalle's invariance theorem proved that almost all trajectories converge asymptotically to the desired equilibrium. Experimental results, obtained with DIY Quad equipped with the APM2.6 auto-pilot, show the effectiveness and the performance of the proposed solutions.
This paper presents an adaptive control strategy for an upper-limb exoskeleton based on an on-line dynamic parameter estimator. The objective is to improve the control performance of this system that plays a critical role in assisting patients for shoulder, elbow and wrist joint movements. In general, the dynamic parameters of the human limb are unknown and differ from a person to another, which degrade the performances of the exoskeleton-human control system. For this reason, the proposed control scheme contains a supplementary loop based on a new efficient on-line estimator of the dynamic parameters. Indeed, the latter is acting upon the parameter adaptation of the controller to ensure the performances of the system in the presence of parameter uncertainties and perturbations. The exoskeleton used in this work is presented and a physical model of the exoskeleton interacting with a 7 Degree of Freedom (DoF) upper limb model is generated using the SimMechanics library of MatLab/Simulink. To illustrate the effectiveness of the proposed approach, an example of passive rehabilitation movements is performed using multi-body dynamic simulation. The aims is to maneuver the exoskeleton that drive the upper limb to track desired trajectories in the case of the passive arm movements.
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