Adaptive stochastic control for linear systems. I - Solution method
Linear discrete time stochastic system with unknown gain parameters, interpreting open loop feedback optimal control identifier and controller equations
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Linear discrete time stochastic system with unknown gain parameters, interpreting open loop feedback optimal control identifier and controller equations
Digital computer approximation of automatic control piecewise linear systems by integral equations
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.
An approximate solution is obtained for a singularly perturbed system of initial valued, time invariant, linear differential equations with multiple boundary layers. Conditions are stated under which the approximate solution converges uniformly to the exact solution as the perturbation parameter tends to zero. The solution is obtained by the method of matched asymptotic expansions. Use of the results for obtaining approximate solutions of general linear systems is discussed. An example is considered to illustrate the method and it is shown that the formulas derived give a readily computed uniform approximation.
Computational worst error algorithm for linear systems and quadratic error criteria, showing flowgraph and computer execution results
In this paper, a linear control design algorithm based on the elemental perturbation bounds developed recently is presented for a simple second order linear uncertain system satisfying matching conditions. The proposed method is compared with Guaranteed Cost Control (GCC), Multistep Guaranteed Cost Control (MGCC) and the Matching Condition (MC) methods and is shown to give guaranteed stability with lesser values for the control gains than some of the existing methods for the example considered.
A block-diagonal linear (not necessarily time-invariant) map P with a right-coprime factorization ND-1 (or a left-coprime factorization D-1N) is considered. It is shown that the individual blocks in P have right-coprime factorizations (left-coprime factorizations, respectively) if and only if the denominator map D has a special block-triangular structure. This condition is applied to the stable linear feedback system S(P1,P2).
A crosscorrelation method of measuring the impulse response of linear systems is presented. The technique, implementation, and limitations of this method are discussed. A simple system is designed and built using discrete components and the impulse response of a linear circuit is measured. Theoretical and software simulation results are presented.
Use of the frobenius series in solving homogeneous linear systems of differential equations with weak singular points
Quadratic invariance of scalar ouput of time varying linear system
Stability indicative function applied to linear systems with multiple delays
Theory and equations on complete controllability of higher order linear systems
Determination of stability indicative function for linear systems with multiple time delays
Discrete time finite dimensional autonomous linear systems, investigating controllability and pole assignment to closed loop transfer matrix by choice of state variable feedback gain
A system for and method of determining an input command profile for substantially any dynamic system that can be modeled as a linear system, the input command profile for transitioning an output of the dynamic system from one state to another state. The present invention involves identifying characteristics of the dynamic system, selecting a command profile which defines an input to the dynamic system based on the identified characteristics, wherein the command profile comprises one or more pulses which rise and fall at switch times, imposing a plurality of constraints on the dynamic system, at least one of the constraints being defined in terms of the switch times, and determining the switch times for the input to the dynamic system based on the command profile and the plurality of constraints. The characteristics may be related to poles and zeros of the dynamic system, and the plurality of constraints may include a dynamics cancellation constraint which specifies that the input moves the dynamic system from a first state to a second state such that the dynamic system remains substantially at the second state.
Optimal control theory is applied to analyze the transient response of discrete linear systems to forcing functions with unknown time dependence but having known bounds. Particular attention is given to forcing functions which include: (1) maximum displacement of any given mass element, (2) maximum relative displacement of any two adjacent masses, and (3) maximum acceleration of a given mass. Linear mechanical systems with an arbitrary number of degrees of freedom and only one forcing function acting are considered. In the general case, the desired forcing function is found to be a function that switches from the upper-to-lower bound and vice-versa at certain moments of time. A general procedure for finding such switching times is set forth.
Here, we propose a solution strategy for the large indefinite linear systems arising in interior methods for nonlinear optimization. The method is suitable for implementation on hardware accelerators such as graphical processing units (GPUs). The current gold standard for sparse indefinite systems is the LBLT factorization where L is a lower triangular matrix and B is 1×1 or 2×2 block diagonal. However, this requires pivoting, which substantially increases communication cost and degrades performance on GPUs. Our approach solves a large indefinite system by solving multiple smaller positive definite systems, using an iterative solver on the Schur complement and an inner direct solve (via Cholesky factorization) within each iteration. Cholesky is stable without pivoting, thereby reducing communication and allowing reuse of the symbolic factorization. We demonstrate the practicality of our approach on large optimal power flow problems and show that it can efficiently utilize GPUs and outperform LBL T factorization of the full system.
Adaptive state vector control - part i, self- evaluating control of linear systems