Showing papers in "Automatica in 1972"

TL;DR: In this article, the problem of assigning physically meaningful measures of the quality of controllability and observability is considered, and three physical measures-determinant, trace, and maximal eigenvalue of the inverse characteristic controLLability or observability matrix-are imbedded in a set of measures which is defined as the set of certain means related to the eigenvalues of the characteristic matrix.

TL;DR: It is shown that the optimal measurement policy and the associated ''matched'' Kalman-type filter can be precomputed, i.e. specified before the measurements actually occur, and numerical results for a third-order system with two possible measurements are presented.

TL;DR: In this paper, the problem of the derivation of simple transfer function models from high-order state variable models is reviewed, and methods of reduction are classified according to whether they involve 1) the computation of the time or frequency responses, 2) the derivations, as an intermediate step, of a transfer function which is the ratio of two polynomials, the denominator being of the same order as the state variable model, or 3) a set of characterising functions.

TL;DR: In this article, the authors formulate and discuss stabilizability of decentralized linear time invariant dynamical systems with coordination and/or communication among control agents, defined as dynamical system with several controllers with partial information on the states of the systems.

TL;DR: In this paper, a review of multivariable feedback system design techniques from the frequency-response viewpoint is given, including a comparison of the advantages and disadvantages of each type of design method, including Non-Interacting Control, Modal Control, Optimal Control, Commutative Control, The Inverse Nyquist Array and The Characteristic Locus.

TL;DR: In this article, a fully computerized cement rotary kiln process control was tested in a real production line and the results are presented in this paper, based on the understanding of the process behavior obtained by careful statistical analyses, and it was realized by using a very efficient statistical identification procedure and the orthodox optimal controller design by the statespace method.

TL;DR: In this article, the invariant structure of a controllable matrix pair (A, B) under a transformation group G, which includes the regular linear coordinate transformations and also transformations of'state feedback' type which take A into A + BF for some F, is studied.

TL;DR: In this paper, a model of a coal/oil flame which takes into account the surrounding temperatures is developed, and the dynamic behavior of the kiln as exhibited by this model is then indicated.

TL;DR: An algorithm is described for recursively calculating the minimal partial repreentations for the sequences R"0,..., R"N, N=0, 1, ..., taken as inputs to the algorithm.

TL;DR: Arbib and Zeiger's generalization of Ho's algorithm for system identification is presented from an alternative viewpoint called ''state characterization'' and it is proposed that state characterization may have practical application in determining an approximate, low order description of a complex system about which the authors have little prior information.

TL;DR: In this paper, a stabilizing feedback control for Haldane-Monod model of microbial growth is designed for stabilizing the growth of a set of microorganisms, which is optimal in the sense that it approaches the maximum production steady state from any initial state.

TL;DR: In this paper, the problem of optimal control of a system whose mathematical model involves dependence on both a history of state type variables and the control variables is considered, and the canonical equations which one obtains by application of a maximum principle for the optimal control problem are transformed into equivalent integral equations which can be solved by use of the Fredholm resolvent theory.

TL;DR: In this paper, the authors compared the performance of different identification methods for the identification of the dynamics of a nuclear reactor, a distillation column, a superheater and a paper machine.

TL;DR: In this article, Luenberger's minimal-order observer is considered as an alternate to the Kalman filter for obtaining state estimates in linear discrete-time stochastic systems and the observer solution is extended to systems for which the noise disturbances are time-wise correlated processes of the Markov type.

TL;DR: In this paper, the problem of finding all nonnegative definite solutions to the ''Riccati'' algebraic equation PA + A'P - PBB'P + C'C = 0 is solved in general.

TL;DR: In this paper, a method for synthesizing suboptimal feedback control laws for nonlinear systems optimized with respect to a quadratic performance index is presented, which allows the designer to easily calculate a second-order approximation to the optimal control.

TL;DR: A new algorithm for the solution of the Parameter-Adaptive Self-Organizing Control Problem is proposed, based on the learning property of the a posteriori probabilities of the parameter estimates, which forces the algorithm to converge to the optimal solution rapidly.

TL;DR: In this article, the formulation of the optimal, linear, time-invariant, multivariable control problem with quadratic performance index is extended so that the solution includes multivariability integral feedback and model-following capabilities in addition to the normal proportional state feedback.

TL;DR: In this article, a bound on the accuracy of causally estimating a Gaussian process from nonlinear observations is derived, where both additive Gaussian noise and Poisson observations are included.

TL;DR: This paper attempts to examine the interdependence of these two problems and to develop an iterative computational approach for solving the joint problem which actually arises in practice; namely, the optimization of a plant whose parameters are in fact unknown.

TL;DR: In this article, a new approach to the design of state estimators for systems with large, but bounded uncertainties in plant and measurement noise covariances is proposed and explored, where a linear estimator with unspecified gain is chosen a priori.

TL;DR: In this paper, the Riccati equation reached equilibrium in finite time in constant or invariant directions of a class of singular, autonomous discrete-time optimization problems, and a control point of view was used to completely characterize the space of constant directions for the case of multi-input control.

TL;DR: It is shown that approximation at the end has no advantage over approximation atThe beginning for the distributed system and the method of approximation considered and the question of obtaining numerical solutions by Galerkin's approximation done at the beginning and at theend is considered.

TL;DR: This paper presents some new research results concerning the sample stability, as opposed to statistical, or ensemble stability, of linear stochastic delay-differential equations.

TL;DR: In this article, a family of variable-altitude turns obtained by numerical integration in the reduced-order approximation is presented for a hypothetical supersonic aircraft, including the effects of constraints on altitude, dynamic pressure, Mach number, lift coefficient, and normal load factor.

TL;DR: In this paper, the authors describe an application of modal analysis for determining the control system of a chemical plant described by 41 linearized differential equations with 8 inputs, where a proportional feedback control system is found so that the dominant time constant of the closed loop system is reduced and then an integral feedback control is found to eliminate the effect of constant unknown disturbances on the system.

TL;DR: In this article, a two-level control structure is proposed to consider all known properties of a plant within an open-loop, feed-forward, upper level control scheme containing a model of the plant to be controlled and a controller which feeds back the model's state vector.

TL;DR: In this article, an optimal control policy for a discrete-time linear system with interrupted observations and an expected quadratic cost is proposed, which is realized by cascading a nonlinear estimator, which computes the conditional mean of the state vector, with the optimal feedback gain matrix in which all uncertainties are removed.

TL;DR: For a completely specified strongly connected synchronous sequential machine, the problem of constructing the input-output sequences that will be sufficient to identify the machine, given its flow table, is first studied and an adaptive procedure is suggested.

TL;DR: In this paper, a modified form of the Leverrier algorithm is presented which has been found satisfactory for matrices whose elements differ by several orders of magnitude, and the results are compared with a method presented by Morgan [4] and a modified version of the leverrier algorithm.