Large, lightweight telescopes in space will enable future earth science, space science, and reconnaissance. The state of the art in space telescope is the Hubble Space Telescope launched in 1990 with its 2.4 m primary mirror. Missions within the decade such as the Next Generation Space Telescope will push this aperture diameter to over 6.5 m. But truly revolutionary observation in many wavelengths will require increasingly large and lightweight apertures. Although these telescopes of the future will have low areal mass density, the deployed aperture structures must capture and hold a surface figure to a fraction of a wavelength in the presence of thermal, slew, and vibration disturbances. Active control of surface figure is a key technology for the success of gossamer space structures. For structures with thousands of actuators distributed in the surface, the control hardware and computations should be distributed as well. This paper discusses how an efficient control of a membrane reflector shape can be achieved using embedded actuators distributed over the membrane surface. Advanced algorithms using only local information about errors and actuation for collocated and neighboring positions in each of the distributed computational elements allow achieving required control performance. Electrostatic actuators implemented on compliant plastic substrates, represent a highly attractive proposition thanks to their very low areal density. Control, sensing, and communication is distributed and integrated in the adaptive membrane to provide the imaging surface quality of a thick stiff mirror at an infinitesimal fraction of the mass. An adaptive membrane with built-in distributed actuators, sensors, and computational elements can be made scalable to a very large size.
This paper considers dynamical transient effects in the physical layer of an optical circuit-switched WDM network. These transients of the average transmission power have millisecond time scales. Instead of studying detailed nonlinear dynamics of the network elements, such as optical line amplifiers, a linearized model of the dynamics around a given steady state is considered. System-level analysis in this paper uses modern control theory methods and handles nonlinearity as uncertainty. The analysis translates requirements on the network performance into the requirements to the network elements. These requirements involve a few gross measures of performance for network elements and do not depend on the circuit switching state. One such performance measure is the worst amplification gain for all harmonic disturbances of the average transmission power. Another, is cross coupling of the wavelength channel power variations. The derived requirements guarantee system-level performance for all network configurations and can be used for specifying optical components and subsystems.
This paper considers control analysis approaches for systems incorporating large actuator and sensor arrays. Applications of such systems are increasingly common because of the development of micro-systems technology. Many imaging systems have large one-dimensional or two-dimensional arrays of actuators. This includes RF or optical reflectors, display, printing, and other systems. Signal processing for large sensor arrays has well-established theory and applications, especially in imaging. At the same time, approaches to control of large distributed actuator and sensor arrays are much less developed. This paper considers one of the fundamental issues in design and analysis of large actuator and sensor array systems. The key notion in modern feedback control theory is the notion of uncertainty and associated notion of control robustness to this uncertainty. In control of dynamical systems evolving in time, structured uncertainty models are commonly accepted for theoretical analysis (Structured Singular Value or (mu) -analysis) and practical control design. In control of spatially distributed processes, there is a need to establish appropriate models of the uncertainty of the system spatial and dynamical characteristics. This paper discusses an extension of structured uncertainty models towards controlled systems with spatially distributed arrays of actuators and sensors. Unlike a dynamical uncertainty, spatial uncertainty is not casual in the spatial coordinate. This leads to related but different uncertainty models in the two cases. For spatial coordinates, boundary effects also contribute to the modeling error. By using the discussed uncertainty models, the existing methods of robust control design and analysis can be extended towards spatially distributed systems. As an illustrative example, this paper demonstrates an application of the developed approach to a one-dimensional model of a flexible reflector with a distrusted actuator array for shape control.