After a brief history of use in space about two decades ago, a resurgence of interest in membrane structures in space is developing, motivated in large part by a great potential for reduced launch mass and stowed volume. Applications for such structures range from planar configurations in solar sails, concentrators and shields, to inflatable lenticulars for radar, radio and optics.Three key factors are paramount for the success and user acceptance of this technology: deployment, longevity and performance. The performance hinges critically on the precision of the membrane surface. The amount of precision is highly mission dependent and may entail one or more of the following issues: surface smoothness, deviation from desired surface profile and slope error. Surface precision is often estimated to be between 1 50 to 1 20 of the wavelength of interest; thus values on the order of a micron (or less) to a millimeter root mean square (RMS) are often presented. It is unlikely that such surface precision can be achieved through purely passive means.This paper addresses the problem of modeling and controlling a class of nonlinear systems that can be considered as highly compliant structures. We consider specifically planar and inflatable membranes, which are represented by complex nonlinear multi-variable models. Boundary perturbations and thermal gradients are demonstrated to be potential actuation schemes for improving the reflector profile. Nonlinear controllers developed to improve performance are often dependent on state estimation and parameter identification procedures. The existence of these procedures, within the control strategy, increases the size of the algorithms, limiting the system performance in real-time. This research has as a main objective to create an intelligent controller based on feedback error learning, which is capable of extracting performance information from precision large membrane deployables and subsequently using this information to achieve maximum surface precision.

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The control of a knee joint in an active above-knee prosthesis has been designed using the Lyapunov tracking method. A simulation of locomotion was done to prove that the tracking control in output space is a valuable real time control method for artificial legs. The data used for simulation was collected in able-bodied subjects while they walked on a powered treadmill. Human volunteers were braced with an ankle splint (limiting dorsi- and plantar flexion) and with a knee cage (limiting knee movements to the lateral plane). We studied the achieved tracking of the prescribed knee motion, deviations of the thigh movement from the prescribed trajectory, maximal angular deviations from the desired trajectory and the power consumption as functions of a limited maximal knee torque and a damping constant in the knee actuator. We found that the use of output tracking method is suitable for the design of appropriate hardware of an above-knee prosthesis and for real-time control.

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