Showing papers in "IFAC Proceedings Volumes in 1964"

TL;DR: In this article, the authors discuss the basic concepts related to optimality, insensitivity, and game theory, and present an attempt to formulate the sensitivity problem in a general way, and explain briefly and qualitatively some of the notions of game theory and how they enter the insensitivity problem and review those theorems which strike as particularly relevant to that problem.

TL;DR: In this paper, the jump conditions for sensitivity coefficients are defined for two-point boundary problems in optimal control syntheses. But at the discontinuity points, the variational equations are not defined.

TL;DR: In this paper, the authors discuss the sensitivity of automatic control systems with variable structure and describe the task of synthesizing control systems for linear plants with variable parameters satisfying specified performance criteria.

TL;DR: The invariant imbedding method can be used to determine information regarding the missing initial conditions as discussed by the authors, which plays a major role in the sensitivity analysis of certain classes of adaptive control systems.

TL;DR: In this paper, the sensitivity of the performance of optimal control systems to plant parameter variations is discussed, and the problem of determining the change in value or a performance index with parameter variations, and a method or computing the performance index sensitivity functions is considered.

TL;DR: The compound control that is obtained by combining the sensitivity criterion with some other criteria of optimality is optimal and less sensitive to small parameter variations.

TL;DR: In this article, a sensitivity analysis based on the modified Krylov-Bogoliubov approach is proposed to obtain information about the relative stability of self-excited oscillations and the transient response of nonlinear control systems.

TL;DR: The chapter presents the application of sensitivity analysis technique to the compensation of quantization errors in hybrid computer systems involving closed-loop interconnections of analog and digital hardware.

TL;DR: In this paper, a precise definition of the notion of system sensitivity and the method of transformed systems is presented, where the possibility of changing parameters is intentionally introduced to achieve adaptation properties as, for example, in optimal and self-adjusting systems.

TL;DR: In this article, the sensitivity of an optimal control system to measurement errors is defined as the value of the minimized expected cost function with respect to the hyperstate variables, and the sensitivity to variations of the statistical description of the state.

TL;DR: This chapter describes the design of self-adjusting control systems by use of a functional derivative technique, whose main part can be implemented by solving differential equations only and there will be no need to store functions, or to invert matrices.

TL;DR: This chapter discusses the structural bases for the solution of sensitivity problems by finding a class of structures and the rules for its synthesis such that the variation of certain parameters will have no influence, or sufficiently small influence on its dynamic properties.

TL;DR: The chapter highlights that every nonlinear SDS must be stable, and it is essential that SDS be able to retain its properties at least under small variations of its parameters and of the external disturbing excitation.

TL;DR: In this article, sensitivity analysis and Lyapunov stability are discussed in the context of a correctly set problem, which admits a solution y 0 not only for an isolated set of parameters, but also in at least a sufficiently small neighborhood of λ 0.

TL;DR: In this paper, a design procedure for achieving compensation to plant parameter variations because of external variables is presented, based on an extension of the concept of sensitivity to that of dependency on several variables.

TL;DR: This chapter describes special problems in the synthesis of sensitivity network and presents the sensitivity to variations in a parameter q of signals in networks of linear transfer functions and instantaneous function generators.

TL;DR: In this article, sensitivity matrices have been used to compare feedback and open loop performances for multi-input, multi-output linear time-invariant systems, and a direct comparison of open and closed loop errors via the sensitivity operator has been presented.

TL;DR: In this article, the necessary and sufficient conditions of parametric invariance were discussed for linear systems subject to stationary or nonstationary variations B(t) of matrix A of a linear system.

TL;DR: In this article, a method of setting up computer circuits for the determination of sensitivity functions with respect to small parameters increasing the order of the system is presented, whereby the passage to the limit λ→0 is performed directly on the model of the non-degenerate systems.

TL;DR: In this paper, structural rules for the determination of sensitivity functions of nonlinear nonstationary systems are discussed, where sensitivity functions are obtained from a sensitivity structure that is determined once for all and that closely resembles the basic structure of the system.

TL;DR: In this article, an attempt is made to apply an optimal stochastic control policy to a realistically flavored dynamical system differing to some extent from the system assumed in the development of the policy.

TL;DR: In this article, the sensitivity considerations for sampled-data feedback systems with a minimal prototype response are discussed, and a self-adjustment method is proposed to reduce the influence of parameters.

TL;DR: This chapter presents the minimum sensitivity adaptive systems, a type of adaptation in which the appropriate adjustment of controller parameters is achieved by online solution of linear algebraic equations.

TL;DR: In this article, the authors present the application of graph theory to the evaluation of sensitivity coefficients of network functions and derive the sensitivity coefficients for the function of a 3-terminal-pair network with respect to variations of one imittance in terms of open-circuit impedance functions.

TL;DR: In this article, a structural interpretation of the logarithmic sensitivity function is proposed for linear systems, where the sensitivity points are defined as those points in the system up to which, starting from the input of the system, the transmittance is equal to the sensitivity function.