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Leondes, C. T.

Publications and source records attributed to Leondes, C. T..

Formulation and implementation of a practical algorithm for non-stationary adaptive state estimation

Background information on the Kalman filter is given first. A discussion of the filter parameters and their a priori determination follows. The discussion points out the need for adaptive determination of the process noise statistics. The filter innovations are presented as a means for developing the adaptive criteria. The criteria center around the estimation of the true mean and covariance of the filter innovations. A method for the numerical approximation of the mean and covariance of a locally stationary random process is presented. The definition of a local stationarity is presented. Local stationarity allows for the separation of the process statistics into a stationary component and a time-varying component. The separation method is discussed. A method for estimating the stationary and time-varying components is presented. As an example of its application to real problems, the algorithm is applied to the problem to the problem of reentry trajectory estimation for the Space Shuttle. Both the adaptive algorithm and the steady-state Kalman filter are applied to the problem. The results of the reconstructions are presented. The adaptive algorithm exhibits superior performance.

Whitemore, S. A.

Application of adaptive control to space stations

The space station will be deployed and assembled in low earth orbit with multiple Shuttle trips. Several construction phases will be required involving both ground and in-orbit operations. In this paper, the construction process of a four-panel space station and its control problems are discussed. The applicability of a direct model reference adaptive control technique with plant augmentation is investigated. Control during several key assembly operation periods has been simulated. These include Shuttle docking with initial-phase station, habitat module mating, and Shuttle docking with operational station. High rate of convergence and robust performance have been observed for all the simulated cases even with 40 percent model parameter errors and model truncations and more than 100 percent instant mass property variations. Controller with severe gain saturations is also discussed and results show only slight performance deterioration.

Ih, C.-H. C.

An investigation of adaptive control techniques for space stations

The present paper is concerned with control problems which arise in connection with the establishment and maintenance of space stations. Some of the arising problems are related to great changes in mass and an intensive shock load accompanying Shuttle docking. Such problems can be solved by making use of a robust adaptive control system. Space station configurations developed by NASA and the corresponding mass properties are discussed along with dynamic models for space stations, aspects of problem formulation and control architecture, adaptive control algorithms, a performance analysis, and practical considerations. Attention is given to adaptive regulator control with initial transient, adaptive control during Shuttle docking, and cases involving Shuttle hard docking with model switching and disturbance modeling.

Ih, C.-H. C.

An identification algorithm for linear stochastic systems with time delays

Linear discrete stochastic control systems containing unknown multiple time delays, plant parameters and noise variances are considered. An algorithm is established which uses the maximum-likelihood technique to identify the unknown parameters. An estimated likelihood function is evaluated based on the previous parameter estimates, which in turn generates a new descent direction vector to update the unknown parameters. The delays and plant parameters are identified in their respective parameter spaces. An example of a second-order stochastic system has been implemented by digital simulation to demonstrate the applicability of the algorithm.

Leondes, C. T.

Sequential filter design for precision orbit determination and physical constant refinement

Earth-based spacecraft tracking data have historically been processed with classical least squares filtering techniques both for navigation purposes and for physical constant determination. The small, stochastic nongravitational forces acting on the spacecraft are described to motivate the use of sequential estimation as an alternative to the least squares fitting procedures. The stochastic forces are investigated both in terms of their effect on the tracking data and their influence on estimation accuracy. A flexible sequential filter design which leaves the existing trajectory, variational equations, data observable and partial computations undisturbed is described. A detailed filter design is presented that meets the precision demands and flexibility requirements of deep space navigation and of scientific problems.

Curkendall, D. W.