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Monopoli, R. V.

Publications and source records attributed to Monopoli, R. V..

At least 19 records

Discrete model reference adaptive systems with measurement noise

A digital computer simulation study is presented for a class of discrete model reference adaptive systems designed using Liapunov's direct method. Plant output measurements are assumed to contain uniformly distributed additive noise. It is shown that the design works well even when such noise is relatively extreme. A new result is presented pertaining to improving the convergence properties of these systems. This result is obtained by modifying the dynamic characteristics of the augmented error equation.

Monopoli, R. V.

Parameter adaptive control of multivariable systems

Model reference adaptive controllers for multivariable plants are designed using only input and output signals rather than the complete state vector. The design is based on Liapunov's direct method, and the Meyer-Kalman-Yacubovich lemma. State variable filters are employed to avoid differentiating output signals. Augmented error signals are used in deriving stable adaptive control laws which assure that the normally used response error signals approach zero asymptotically.

Monopoli, R. V.

On the stabilization of bilinear systems via hyperstability

The problem of feedback stabilization for continuous and discrete bilinear systems is investigated. Attention is also given to the 'drift' term case to take into account physical systems in which preassigned values are imposed on some of the controls. A proposed set of controls for asymptotic stabilization is applicable to a fairly large class of bilinear systems. It is pointed out that the results presented can be used to design nonlinear adaptive controllers which in some cases are preferable to linear controllers.

Ionescu, T.

Model reference adaptive control with an augmented error signal

It is shown how globally stable model reference adaptive control systems may be designed when one has access to only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Lyapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Derivatives of the plant output are not required, but are replaced by filtered derivative signals. An augmented error signal replaces the error normally used, which is defined as the difference between the model and plant outputs. However, global stability is assured in the sense that the normally used error signal approaches zero asymptotically.

Monopoli, R. V.

Linear system identification - The application of Lion's identification scheme to a third order system with noisy input-output measurements

A linear system identification technique developed by Lion is adapted for use on a third-order system with six unknown parameters and noisy input-output measurements. A digital computer is employed so that rapid identification takes place with only two state variable filters. Bias in the parameter estimates is partially eliminated by a signal-to-noise ratio testing procedure.

Brown, C. M., Jr.

An experimental study of a hybrid adaptive control system

A Liapunov type model reference adaptive control system with five adjustable gains is implemented using a PDP-11 digital computer and an EAI 380 analog computer. The plant controlled is a laboratory type dc servo system. It is made to follow closely a second order linear model. The experimental results demonstrate the feasibility of implementing this rather complex design using only a minicomputer and a reasonable number of operational amplifiers. Also, it points out that satisfactory performance can be achieved even when certain assumptions necessary for the theory are not satisfied.

Lizewski, E. F.

The Kalman-Yacubovich lemma in adaptive control system design.

New results are presented that pertain to the design of model-reference adaptive control systems with the aid of the Kalman-Yacubovich lemma derived in connection with the problem of Lure. It is shown that the Kalman-Yacubovich lemma is a much more powerful tool for designing model-reference adaptive control systems than was previously thought.

Monopoli, R. V.

Model reference adaptive control using only input and output signals

It is shown how globally stable model reference adaptive control systems may be designed using only the plant's input and output signals. Controllers for single input-single output, nonlinear, nonautonomous plants are developed based on Liapunov's direct method and the Meyer-Kalman-Yacubovich lemma. Filtered derivatives of the plant output replace pure derivatives which are normally required in these systems. An augmented error signal replaces the error previously used which is the difference between the model and plant outputs. However, global stability is assured in the sense that this difference approaches zero asymptotically.

Monopoli, R. V.

An improved design technique for parameter adaptive control systems.

A parameter adaptive control technique is developed utilizing Liapunov's Direct Method. The design approach represents an improvement over previous methods in that only one derivative network is required for controller implementation. Furthermore, the technique may be applied to plants with right half plane zeros while maintaining a bounded control input.

Gilbart, J. W.

Adaptive control and identification via Liapunov's direct method.

The adaptive control and identification problems for single input, single output, time invariant systems with unknown parameters are considered here. A model reference is used and Liapunov's direct method provides the mechanisms for deriving the adaptive and identification algorithms. The Kalman Lemma (derived in connection with the Lure' problem) is shown to be extremely helpful in the design of these systems.

Monopoli, R. V.