A computer-aided design package for nonlinear model applications
Explore the source record for details and available documents.
Engineering topics
Publications and source records attributed to Sain, M. K..
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Some computational issues associated with the calcualtion of optimal feedback controls for nonlinear systems in a tensor setting are described. The specific issues addressed pertain to the combinatorial nature of the loading of the elements into tensors used to represent the system, cost, and feedback, and the subsequent calculations involving these elements. Particular attention is given to: the symmetric tensor algebra which is a natural setting for representing polynomials; the conversions between symmetric and nonsymmetric tensors; the general nature of the calculations required; and the solution equation for nonlinear optimal feedback control. It is concluded that nonlinear tensor feedback can improve performance both in terms of system responses and in terms of system stability region.
The technical progress of researches Alternatives for Jet Engine Control is reported. A numerical study employing feedback tensors for optimal control of nonlinear systems was completed. It is believed that these studies are the first of their kind. State regulation, with a decrease in control power is demonstrated. A detailed treatment follows.
The technical progress of researches on alternatives for jet engine control is reported. Extensive numerical testing is included. It is indicated that optimal inputs contribute significantly to the process of calculating tensor approximations for nonlinear systems, and that the resulting approximations may be order-reduced in a systematic way.
The technical progress of researches on alternatives for jet engine control, is reported. The principal new activities involved the initial testing of an input design method for choosing the inputs to a non-linear system to aid the approximation of its tensor parameters, and the beginning of order reduction studies designed to remove unnecessary monomials from tensor models.
Tensor model order reduction, recursive tensor model identification, input design for tensor model identification, software development for nonlinear feedback control laws based upon tensors, and development of the CATNAP software package for tensor modeling, identification and simulation were studied. The last of these are discussed.
The development of models of tensor type for a digital simulation of the quiet, clean safe engine (QCSE) gas turbine engine; the extension, to nonlinear multivariate control system design, of the concepts of total synthesis which trace their roots back to certain early investigations under this grant; the role of series descriptions as they relate to questions of scheduling in the control of gas turbine engines; the development of computer-aided design software for tensor modeling calculations; further enhancement of the softwares for linear total synthesis, mentioned above; and calculation of the first known examples using tensors for nonlinear feedback control are discussed.
The Nominal Design Problem (NDP) is extended to nonlinear cases, and a new case study of robust feedback synthesis for gas turbine control design is presented. The discussion of NDP extends and builds on earlier Total Synthesis Problem theory and ideas. Some mathematical preliminaries are given in which a bijection from a set S onto a set T is considered, with T admitting the structure of an F-vector space. NDP is then discussed for a nonlinear plant, and nonlinear nominal design is defined and characterized. The design of local controllers for a turbojet and the scheduling of these controls into a global control are addressed.
An application of tensor modelling to a digital simulation of NASA's Quiet, Clean, Shorthaul Experimental (QCSE) gas turbine engine is presented. The results show that the tensor algebra offers a universal parametrization which is helpful in conceptualization and identification for plant modelling prior to feedback or for representing scheduled controllers over an operating line.
Research centered on basic topics in the modeling and feedback control of nonlinear dynamical systems is reported. Of special interest were the following topics: (1) the role of series descriptions, especially insofar as they relate to questions of scheduling, in the control of gas turbine engines; (2) the use of algebraic tensor theory as a technique for parameterizing such descriptions; (3) the relationship between tensor methodology and other parts of the nonlinear literature; (4) the improvement of interactive methods for parameter selection within a tensor viewpoint; and (5) study of feedback gain representation as a counterpart to these modeling and parameterization ideas.
Zames (1981) has observed that there is, in general, no 'separation principle' to guarantee optimality of a division between control law design and filtering of plant uncertainty. Peczkowski and Sain (1978) have solved a model matching problem using transfer functions. Taking into consideration this investigation, Peczkowski et al. (1979) proposed the Total Synthesis Problem (TSP), wherein both the command/output-response and command/control-response are to be synthesized, subject to the plant constraint. The TSP concept can be subdivided into a Nominal Design Problem (NDP), which is not dependent upon specific controller structures, and a Feedback Synthesis Problem (FSP), which is. Gejji (1980) found that NDP was characterized in terms of the plant structural matrices and a single, 'good' transfer function matrix. Sain et al. (1981) have extended this NDP work. The present investigation is concerned with a study of FSP for the unity feedback case. NDP, together with feedback synthesis, is understood as a Total Synthesis Problem.
Alternatives to linear quadratic regulator theory in the linear case are examined along with nonlinear modelling and optimization approaches for global control. Context for the studies has been set by the DYNGEN digital simulator and by models generated for various phases of the F100 Multivariable Control Synthesis Program. With respect to the linear alternatives, the multivariable frequency domain is stressed. Progress is reported in both the direct algebraic approach to exact model matching, by means of stimulating work on the basic computational issues, and in the indirect generalized Nyquist approach. With respect to nonlinear modelling and optimization, the emphasis is twofold: the development of analytical nonlinear models of the jet engine and the use of these models in conjunction with techniques of mathematical programming in order to study global control over nonincremental portions of the flight envelope. The possibility of using tensor methods is explored.
Nonlinear modeling researches involving the use of tensor analysis are presented. Progress was achieved by extending the studies to a controlled equation and by considering more complex situations. Included in the report are calculations illustrating the modeling methodology for cases in which variables take values in real spaces of dimension up to three, and in which the degree of tensor term retention is as high as three.
The paper presents the CARDIAD (complex acceptability region for diagonal dominance) method for achieving the diagonal dominance condition in the inverse Nyquist array approach to the analysis and design of multivariable systems in the frequency domain. A design example is given for a sixth order, 4-input, 4-output model of a turbofan engine.
The research is classified in two categories: (1) the use of modern multivariable frequency domain methods for control of engine models in the neighborhood of a set-point, and (2) the use of nonlinear modelling and optimization techniques for control of engine models over a more extensive part of the flight envelope. Progress in the first category included the extension of CARDIAD (Complex Acceptability Region for Diagonal Dominance) methods developed with the help of the grant to the case of engine models with four inputs and four outputs. A suitable bounding procedure for the dominance function was determined. Progress in the second category had its principal focus on automatic nonlinear model generation. Simulations of models produced satisfactory results where compared with the NASA DYNGEN digital engine deck.