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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Algorithms for adaptive stochastic control for a class of linear systems

Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.

Toda, M.↗
NASA NTRS1988

Design of feedback control systems for unstable plants with saturating actuators

A new control design methodology is introduced for multi-input/multi-output systems with unstable open loop plants and saturating actuators. A control system is designed using well known linear control theory techniques and then a reference prefilter is introduced so that when the references are sufficiently small, the control system operates linearly as designated. For signals large enough to cause saturations, the control law is modified in such a way to ensure stability and to preserve, to the extent possible, the behavior of the linear control design. Key benefits of this methodology are: the modified feedback system never produces saturating control signals, integrators and/or slow dynamics in the compensator never windup, the directionaL properties of the controls are maintained, and the closed loop system has certain guaranteed stability properties. The advantages of the new design methodology are illustrated in the simulation of an approximation of the AFTI-16 (Advanced Fighter Technology Integration) aircraft multivariable longitudinal dynamics.

Kapasouris, Petros↗
NASA NTRS1959

Ground Simulator Studies of a Nonlinear Linkage in a Power Control System

An investigation was made to determine the characteristics of a nonlinear linkage installed in a power control system incorporated in a ground simulator. The nonlinear linkage provided for increased control-stick motion for relatively small simulator response at control motions near neutral. The quality of the control system was rated on the ease and precision with which various tracking tasks were performed by the pilots who operated the simulator. The results obtained with the nonlinear linkage installed in the control system were compared with those obtained by using the normal linear control system. Several combinations of nonlinearity of the linkage were tested for various dynamic characteristics of the simulator. It was found that the pilots were able to track almost as well with the nonlinear linkage installed as with the normal system. All of the pilots were of the opinion, however, that the nonlinearity was an undesirable feature in the control system because of the apparent lack of simulator response through the neutral range of the linkage where relatively large stick deflections could be made with very little simulator motion. The results showed that increased lag between the target and chair position, higher stick-force levels, and uneven stick forces due to the dynamics of the linkage were general characteristics of all the nonlinear linkage conditions tested. It was also found that for cases of low simulator damping, rapid control motions caused considerably higher overshoots when the nonlinear linkage was installed than were obtained for the normal linear control system. These characteristics were considered to be sufficiently undesirable to out-weigh the advantages to be gained from the use of a nonlinear linkage in the control system of an airplane.

Assadourian, Arthur↗
NASA NTRS1980

Linear stochastic optimal control and estimation problem

Problem involves design of controls for linear time-invariant system disturbed by white noise. Solution is Kalman filter coupled through set of optimal regulator gains to produce desired control signal. Key to solution is solving matrix Riccati differential equation. LSOCE effectively solves problem for wide range of practical applications. Program is written in FORTRAN IV for batch execution and has been implemented on IBM 360.

Geyser, L. C.↗
NASA NTRS1973

Frequency control circuit for all-digital phase-lock loops

Phase-lock loop references all its operations to fixed high-frequency service clock operating at highest speed which digital circuits permit. Wide-range control circuit provides linear control of frequency of reference signal. It requires only two counters in combination with control circuit consisting only of flip-flop and gate.

Anderson, T. O.↗
NASA NTRS1976

Linear stochastic optimal control and estimation

Digital program has been written to solve the LSOCE problem by using a time-domain formulation. LSOCE problem is defined as that of designing controls for linear time-invariant system which is disturbed by white noise in such a way as to minimize quadratic performance index.

Geyser, L. C.↗
NASA NTRS1984

The effects of time delay in man-machine control systems: Implications for design of flight simulator Visual-Display-Delay compensation

When human operators are performing precision tracking tasks, their dynamic response can often be modeled by quasilinear describing functions. That fact permits analysis of the effects of delay in certain man machine control systems using linear control system analysis techniques. The analysis indicates that a reduction in system stability is the immediate effect of additional control system delay, and that system characteristics moderate or exaggerate the importance of the delay. A selection of data (simulator and flight test) consistent with the analysis is reviewed. Flight simulator visual-display delay compensation, designed to restore pilot aircraft system stability, was evaluated in several studies which are reviewed here. The studies range from single-axis, tracking-task experiments (with sufficient subjects and trials to establish the statistical significance of the results) to a brief evaluation of compensation of a computer generated imagery (CGI) visual display system in a full six degree of freedom simulation. The compensation was effective, improvements in pilot performance and workload or aircraft handling qualities rating (HQR) were observed. Results from recent aircraft handling qualities research literature, which support the compensation design approach, are also reviewed.

Crane, D. F.↗
NASA NTRSDate not supplied

An L1 Adaptive Control Augmentation for a Lift Plus-Cruise Vehicle

This paper presents anL1adaptive control augmentation for a Lift-Plus-Cruise (L+C)vehicle. This class of vehicles operates in three flight modes with different dynamic behavior: vertical, transition, and forward flight. A robust uniform controller is used as a baseline to stabilize the system throughout these flight modes. The uniform controller is a linear control law designed around trim conditions of the aircraft and includes control allocation to achieve the desired forces and moments on the vehicle. TheL1control augmentation is designed for each of these trim conditions to compensate for the nonlinear time- and state-dependent uncertainties in the vehicle dynamics. The augmented control output is then added to the desired force and moment commands on the vehicle. Simulation results demonstrate the effectiveness of control augmentation for reducing the effects of unmodeled dynamics, reduced actuator effectiveness, and time-dependent disturbances. Effectiveness is demonstrated through tracking error metrics.

Andrew Patterson↗
NASA NTRS1983

Finite-dimensional discrete-time control of linear distributed parameter systems

Systems described by partial differential equations have an infinite-dimensional state space. Feedback control of such distributed parameter systems must be accomplished by finite-dimensional controllers to be implemented by on-line digital computers. A further practical constraint is that the controller must operate in discrete (rather than continuous) time. This paper investigates the stability of such distributed parameter feedback controllers in closed-loop with the actual system.

Balas, M. J.↗
NASA NTRS1967

Modeling with Liapunov functions.

Behavior of high-order linear control systems analyzed using liapunov second method, by finding low-order model with closely approximate response behavior of high order linear control systems analyzed, using Liapunov second method, by finding low order model with closely approximate response

LIAPUNOV FUNCTION↗
NASA NTRS1992

Robust stability and control of linear and multilinear interval systems

This paper is a survey of recent results obtained by the authors and their coworkers on the robust stability and control of systems containing parametric uncertainty. The starting point is a generalization of Kharitonov's theorem obtained by Chapellat and Bhattacharyya in 1989. This theorem, called the Linear CB theorem, its generalization to the multilinear case, the singling out of extremal stability subsets, and other ramifications now constitute an extensive and coherent theory of robust parametric stability that is summarized in the results contained here.

Bhattacharyya, S. P.↗
NASA NTRS1993

Nonlinear rescaling of control values simplifies fuzzy control

Traditional control theory is well-developed mainly for linear control situations. In non-linear cases there is no general method of generating a good control, so we have to rely on the ability of the experts (operators) to control them. If we want to automate their control, we must acquire their knowledge and translate it into a precise control strategy. The experts' knowledge is usually represented in non-numeric terms, namely, in terms of uncertain statements of the type 'if the obstacle is straight ahead, the distance to it is small, and the velocity of the car is medium, press the brakes hard'. Fuzzy control is a methodology that translates such statements into precise formulas for control. The necessary first step of this strategy consists of assigning membership functions to all the terms that the expert uses in his rules (in our sample phrase these words are 'small', 'medium', and 'hard'). The appropriate choice of a membership function can drastically improve the quality of a fuzzy control. In the simplest cases, we can take the functions whose domains have equally spaced endpoints. Because of that, many software packages for fuzzy control are based on this choice of membership functions. This choice is not very efficient in more complicated cases. Therefore, methods have been developed that use neural networks or generic algorithms to 'tune' membership functions. But this tuning takes lots of time (for example, several thousands iterations are typical for neural networks). In some cases there are evident physical reasons why equally space domains do not work: e.g., if the control variable u is always positive (i.e., if we control temperature in a reactor), then negative values (that are generated by equal spacing) simply make no sense. In this case it sounds reasonable to choose another scale u' = f(u) to represent u, so that equal spacing will work fine for u'. In the present paper we formulate the problem of finding the best rescaling function, solve this problem, and show (on a real-life example) that after an optimal rescaling, the un-tuned fuzzy control can be as good as the best state-of-art traditional non-linear controls.

Vanlangingham, H.↗
NASA NTRS2012

Adaptive Control of Linear Modal Systems Using Residual Mode Filters and a Simple Disturbance Estimator

Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.

Balas, Mark↗