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The paper presents a hybrid state-space self-tuner using a new dual-rate sampling scheme for digital adaptive control of continuous-time uncertain linear systems. A state-space-based recursive least-squares algorithm, together with a variable forgetting factor, is used for direct estimations of both the equivalent discrete-time uncertain linear system parameters and the associated discrete-time state of a continuous-time uncertain linear system from the sampled input and output data. An analogue optimal regional pole-placement design method is used for designing an optimal observer-based analogue controller. A suboptimal observer-based digital controller is then designed from the designed analogue controller using digital redesign technique. To enhance the robustness of parameter identification and state estimation algorithms, a dynamic bound for a class of uncertain bilinear parameters and a fast-rate digital controller are developed at each fast-sampling period. Also, to accommodate computation loads and computation delay for developing the advanced hybrid self-tuner, the designed analogue controller and observer gains are both updated at each slow-sampling period. This control technique has been successfully applied to benchmark control problems.

This paper presents a hybrid state-space self-tuning design methodology using dual-rate sampling for suboptimal digital adaptive control of attitude and momentum management for the Space Station. This new hybrid adaptive control scheme combines an on-line recursive estimation algorithm for indirectly identifying the parameters of a continuous-time system from the available fast-rate sampled data of the inputs and states and a controller synthesis algorithm for indirectly finding the slow-rate suboptimal digital controller from the designed optimal analog controller. The proposed method enables the development of digitally implementable control algorithms for the robust control of Space Station Freedom with unknown environmental disturbances and slowly time-varying dynamics.

An adaptive control approach is investigated for the Space Station. The main components of the adaptive controller are the parameter identification scheme, the control gain calculation, and the control law. The control law is the Space Station baseline control law. The control gain calculation is based on linear quadratic regulator theory with eigenvalue placement in a vertical strip. The parameter identification scheme is a real-time recursive extended Kalman filter which estimates the inertias and also provides an estimate of the unmodeled disturbances due to the aerodynamic torques and to the nonlinear effects. An analysis of the inertia estimation problem suggests that it is possible to compute accurate estimates of the Space Station inertias during nominal CMG (control moment gyro) operations. The closed-loop adaptive control law is shown to be capable of stabilizing the Space Station after large inertia changes. Results are presented for the pitch axis.

Based on the algebraic Riccati equation approach, this paper presents a simple and flexible method for designing observer-based robust-H-infinity control laws for linear systems with structured parameter uncertainty. The observer-based robust-H-infinity output-feedback control law, obtained by solving three augmented algebraic Riccati equations, provides both robust stability and disturbance attenuation with H-infinity-norm bound for the closed-loop uncertain linear system. Several tuning parameters are embedded into the augmented algebraic Riccati equations so that flexibility in finding the symmetric positive-definite solutions (and hence, the robust-H-infinity control laws) is significantly increased. A benchmark problem associated with a mass-spring system, which approximates the dynamics of a flexible structure, is used to illustrate the design methodologies, and simulation results are presented.

This paper presents a linear quadratic regulator approach to the stabilization of uncertain linear systems. The uncertain systems under consideration are described by state equations with the presence of time-varying unknown-but-bounded uncertainty matrices. The method is based on linear quadratic regulator (LQR) theory and Liapunov stability theory. The robust stabilizing control law for a given uncertain system can be easily constructed from the symmetric positive-definite solution of the associated augmented Riccati equation. The proposed approach can be applied to matched and/or mismatched systems with uncertainty matrices in which only their matrix norms are bounded by some prescribed values and/or their entries are bounded by some prescribed constraint sets. Several numerical examples are presented to illustrate the results.

This paper presents a multistage design scheme for determining an optimal control-moment-gyro momentum-management and attitude-control system for the Space Station Freedom. The Space Station equations of motion are linearized and block-decomposed into two block-decoupled subsystems using the matrix-sign algorithm. A sequential procedure is utilized for designing a linear-quadratic regulator for each subsystem, which optimally places the eigenvalues of the closed-loop subsystem in the region of an open sector, bounded by lines inclined at + or - pi/2k (for k = 2 or 3) from the negative real axis, and the left-hand side of a line parallel to the imaginary axis in the s-plane. Simulation results are presented to compare the resultant designs.

This paper presents a new sequential design procedure for determining an optimal CMG (control moment gyro) momentum management and attitude control system for the Space Station Freedom. First, the Space Station equations of motion are linearized and uncoupled, and the associated state space equations are defined. Next, a new sequential procedure is used for the development of a continuous quadratic regulator with eigenvalue placement in a specified region of the complex plane. The regional pole assignment method is utilized since it is best suited for tradeoffs between eigenvalue locations and robustness with respect to parameter variations, sensor failures, implementation accuracies and gain reductions. The matrix sign function is used for solving the Riccati equations which appear in the design procedure. Simulation results are given which show that the resultant design provides desired system performance.

A computationally efficient algorithm for the dynamics of multi-rigid-link mechanisms is presented which is applicable to on-board processing for robotic manipulator control systems. A formulation of the equations of motion for such systems is presented which results in a solution algorithm of the order the number of system degrees of freedom. The formulation is presented for tree topology systems, where the chain topology of typical manipulators is a subset. Comparison of this algorithm is made with existing multibody simulation programs to illustrate the increased computational efficiency.

A new digital redesign technique is developed for determining the digital version of an optimal momentum management controller previously designed by the authors for the Space Station Freedom. The technique matches all the states at all sampling instants to find a pseudo-continuous time quadratic regulator. It is shown that the redesigned digital states closely match the continuous time optimal states. It is also shown how the redesign technique can be applied to a state estimator.

The paper discusses a multivariate controller design for a control configured space station concept. The space station concept is novel in that mechanical filters (soft couplers) are used to reduce structural interaction between adjacent modules. The primary objective of this study is to provide stability augmentation to the soft coupled configuration. The control objective is achieved by a state feedback compensator design. To obtain the desired feedback gains, a modified LQR technique is developed which provides prescribed close-loop frequencies and damping ratios.

The paper discusses a multivariable controller design for a control configured space station concept. The space station concept is novel in that mechanical filters (soft couplers) are used to reduce structural interaction between adjacent modules. The primary objective of this study is to provide stability augmentation to the soft coupled configuration. The control objective is achieved by a state feedback compensator design. To obtain the desired feedback gains, a modified LQR technique is developed which provides prescribed close-loop frequencies and damping ratios.

Previously cited in issue 19, p. 2996, Accession no. A82-38960

Certain problems arise in connection with the design and construction of a Space Station. These problems are partly related to the impossibility to predict in advance the ultimate form and size which the Space Station will assume. Due to the abatement of volume and strength constraints it will be desirable (for maximum utility of mass) to permit very low structural resonance frequencies, and due to complexity of the configuration there will be an extremely high density of modal frequencies. The basic approaches available to an attitude control system designer for coping with the dynamics of a plant with the considered characteristics are examined. In order to overcome difficulties related to a use of currently widely considered approaches, a technique is proposed whereby the degrees of freedom requiring active control are isolated mechanically from other superfluous vibratory modes.

An overview of the ascent trajectory and GN&C (guidance, navigation, and control) system design is followed by a summary of flight test results for the ascent phase of STS-1. The most notable variance from nominal pre-flight predictions was the lofted trajectory observed in first stage due to an unanticipated shift in pitch aerodynamic characteristics from those predicted by wind tunnel tests. The GN&C systems performed as expected on STS-1 throughout powered flight. Following a discussion of the software constants changed for Flight 2 to provide adequate performance margin, a summary of test results from STS-2 and STS-3 is presented. Vehicle trajectory response and GN&C system behavior were very similar to STS-1. Ascent aerodynamic characteristics extracted from the first two test flights were included in the data base used to design the first stage steering and pitch trim profiles for STS-3.