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A new method for calculating the coefficients of the numerator polynomial of the direct Routh approximation method (DRAM) using the least square error criterion is formulated. The necessary conditions have been obtained in terms of algebraic equations. The method is useful for low frequency as well as high frequency reduced-order models.
This paper describes a frequency-domain method for the estimation of the aeroelastic equations of motion of an aircraft using discrete sinusoidal inputs to the control surface actuators. The theory of estimation of the signal inputs and outputs is described as well as the method of obtaining accurate transfer functions from the resulting Bode plots. Methods of quantifying the accuracy of the results from more than one control input are discussed along with ways to obtain state-space and reduced-order models from the transfer function estimates. Presented is a summary of the results obtained in using the technique to develop a model of the USAF Total In-Flight Simulator (TIFS) aircraft which includes five symmetrical elastic modes of motion of the aircraft.
A brief analytic exposition is presented to illustrate a central principle in flexible mode control, some of the pertinent pilot centered requirements are listed and discussed. The desired features of the control methodology are exposed and the methodology to be used is selected. The example Boeing supplied characteristics are discussed and approximated with a reduced order model and a simplified treatment of unsteady aerodynamics. The closed loop flight control system design follows, along with first level assessments of resulting handling and ride quality characteristics. Some of these do not meet the postulated requirements and remain problems to be solved possibly by further analysis or future simulation.
The Kreisselmeier discrete adaptive observer is analyzed for the case in which the observer order is less than that of the plant. The state and parameter estimates from the observer are compared to the states and parameters for an arbitrary reduced-order model (ROM) of the plant, where the observer and ROM are of equal dimension. Conditions sufficient for ultimate boundedness of the observation errors are given, and expressions for the error bounds are derived.
A substructure synthesis procedure applicable to structural systems containing general nonconservative terms is presented. In their final form, the non-self-adjoint substructure equations of motion are cast in state vector form through the use of a variational principle. A reduced-order model for each substructure is implemented by representing the substructure as a combination of a small number of Ritz vectors. For the method presented, the substructure Ritz vectors are identified as a truncated set of substructure eigenmodes, which are typically complex, along with a set of generalized real attachment modes. The formation of the generalized attachment modes does not require any knowledge of the substructure flexible modes; hence, only the eigenmodes used explicitly as Ritz vectors need to be extracted from the substructure eigenproblem. An example problem is presented to illustrate the method.
The methods presented are based on results from infinite dimensional control theory, but they can be described and used in a finite dimensional context. This blend leads to an approach which employs powerful ideas on convergence, and is also quite practical for systems of realistic complexity. Appropriate reduced order models are generated simultaneously with the development of the compensator. The required models change as a function of changes in the performance demanded, sensor and actuator location, inherent damping, disturbances, etc. Thus they are driven by the control and estimation problems at hand. The compensators which emerge are very close to the ideal compensators which would be obtained with a very large order model. However, some simplification is frequently possible. The method of balanced realizations was found to be effective for this purpose.
Numerous spacecraft missions currently being formulated exhibit several basic and sharply conflicting features: selected components (e.g., an optical train) of inherently flexible structures are to maintain precision pointing performance in a wideband disturbance environment. Within the overall process of synthesizing an active controller to deal with this difficult problem, the aspects of reduced-order modelling and of actuator and sensor selection are crucial to the successful implementation of any controller feedback strategy. The principal focus in this paper is on the influence of actuator and sensor selection upon the effectiveness of a specified controller strategy for wideband disturbance accommodation. A genetic optical support structure is used for a number of design examples. Active transducer selections are made systematically based upon their direct contributuion to optical pointing error. Controller designs incorporating the various transducer selections exhibit stability in the presence of unmodeled modes over a frequency range substantially beyond the bandwidth of the disturbance.
It is pointed out that the study of systems evolving at multiple time-scales is simplified by studying reduced-order models of these systems valid at specific time-scales. The present investigation is concerned with an extension of results on the time-scale decomposition of autonomous systems to that of input-output systems. The results are employed to study conditions under which positive realness of a transfer function is preserved under singular perturbation. Attention is given to the perturbation theory for linear operators, the multiple time-scale structure of autonomous linear systems, the input-output description of two time-scale linear systems, the positive realness of two time-scale systems, and multiple time-scale linear systems.
Singular perturbation techniques are used in this paper to develop a two time scale procedure for designing static gain output feedback controllers. It is shown that, if certain control spillover conditions are satisfied, control designs based on reduced-order models will stabilize the corrgsponding full system. Optimal output feedback control theory is used to derive the necessary conditions for the stabilizing gain matrix. The problem of stabilizing a model for a large space structure is used to illustrate the practicality of the approach.
The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.
This paper summarizes several applications of Lanczos vectors and Krylov vectors. Lanczos vectors or Krylov vectors for use in component synthesis, Lanczos vectors for systems with unsymmetric damping (unsymmetric Block-Lanczos method), and the use of Lanczos vectors to obtain reduced-order models for control of flexible structures. For each of the above applications the theoretical background is briefly summarized and a numerical example is given.
The existing q-Markov COVER realization theory does not take into account the problems of arithmetic errors due to both the quantization of states and coefficients of the reduced order model. All q-Markov COVERs allow some freedom in the choice of parameters. Here, researchers exploit this freedom in the existing theory to optimize the models with respect to these finite wordlength effects.
A set of linearized equations of motion to predict the linearized dynamic response of a single rotor helicopter in a hover trim condition to cyclic pitch control inputs is described. The equations of motion assume four fuselage degrees of freedom: lateral and longitudinal translation, roll angle, pitch angle: four rotor degrees of freedom: flapping (lateral and longitudinal tilt of the tip path plane), lagging (lateral and longitudinal displacement of the rotor plane center of mass); and dynamic inflow (harmonic components). These ten degrees of freedom correspond to a system with eighteen dynamic states. In addition to examination of the full system dynamics, the computer code supplied with this report permits the examination of various reduced order models. The code is presented in a specific form such that the dynamic response of a helicopter in flight can be investigated. With minor modifications to the code the dynamics of a rotor mounted on a flexible support can also be studied.
An approach is developed using experimental data to identify a reduced-order model and its model error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the Eigensystem Realization Algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole placement technique in combination with a H(infinity) control method is applied to design a controller for the considered system. A set experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach.
A novel approach is developed using experimental data from the structural testing of a physical system to identify a reduced-order model and its error for a robust controller design. There are three steps involved in the approach. First, an approximately balanced model is identified using the eigensystem realization algorithm, which is an identification algorithm. Second, the model error is calculated and described in frequency domain in terms of the H(infinity) norm. Third, a pole-placement technique in combination with an H(infinity) control method is applied to design a controller for the system. A set of experimental data from an existing setup, namely the Mini-Mast system, is used to illustrate and verify the approach development in this paper.
Approaches to the combined design of structures and controllers for achieving optimal maneuverability are presented. A maneuverability index which directly reflects the minimum time required to perform a given set of maneuvers is introduced. By designing the flexible appendages, the maneuver time of the spacecraft is minimized under the constraints of structural properties, and post maneuver spillover is kept within a specified bound. The spillover reduction is achieved by making use of an appropriate reduced order model. The distributed parameter design problem is approached using assumed shape functions, and finite element analysis with dynamic reduction. Solution procedures have been investigated. Approximate design methods have been developed to overcome the computational difficulties. Some new constraints on the modal frequencies of the spacecraft are introduced in the original optimization problem to facilitate the solution process. It is shown that the global optimal design may be obtained by tuning the natural frequencies to satisfy specific constraints. Researchers quantify the difference between a lower bound to the solution for maneuver time associated with the original problem and the estimate obtained from the modified problem, for a specified application requirement. Numerical examples are presented to demonstrate the capability of this approach.
We discuss the application of Generalized Parity Relations to two experimental flexible space structures, the NASA Langley Mini-Mast and Marshall Space Flight Center ACES mast. We concentrate on the generation of residuals and make no attempt to implement the Decision Function. It should be clear from the examples that are presented whether it would be possible to detect the failure of a specific component. We derive the equations from Generalized Parity Relations. Two special cases are treated: namely, Single Sensor Parity Relations (SSPR) and Double Sensor Parity Relations (DSPR). Generalized Parity Relations for actuators are also derived. The NASA Langley Mini-Mast and the application of SSPR and DSPR to a set of displacement sensors located at the tip of the Mini-Mast are discussed. The performance of a reduced order model that includes the first five models of the mast is compared to a set of parity relations that was identified on a set of input-output data. Both time domain and frequency domain comparisons are made. The effect of the sampling period and model order on the performance of the Residual Generators are also discussed. Failure detection experiments where the sensor set consisted of two gyros and an accelerometer are presented. The effects of model order and sampling frequency are again illustrated. The detection of actuator failures is discussed. We use Generalized Parity Relations to monitor control system component failures on the ACES mast. An overview is given of the Failure Detection Filter and experimental results are discussed. Conclusions and directions for future research are given.
The order reduction problem of z-transfer functions is solved by using the multipoint Jordan continued-fraction expansion (MJCFE) technique. An efficient algorithm that does not require the use of complex algebra is presented for obtaining an MJCFE from a stable z-transfer function with expansion points selected from the unit circle and/or the positive real axis of the z-plane. The reduced-order models are exactly the multipoint Pade approximants of the original system and, therefore, they match the (weighted) time-moments of the impulse response and preserve the frequency responses of the system at some characteristic frequencies, such as gain crossover frequency, phase crossover frequency, bandwidth, etc.