摘要:

This paper is concerned with the application of interconnected learning automata to the control of unknown stochastic dynamic systems. A method of usingNlearning automata and subsets of actions to search for optimum controller parameters according to a given performance index is presented. The methodology has been applied as an on-line control strategy for control of an unknown turbogenerator system in noise environments without persistent excitation signals. Simulation results are included.

ISSN:0020-7179    

DOI:10.1080/00207179508921531

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

A discrete-lime ‘universal regulator’ which can adaptively stabilize unknown linear time-invariant (LTI) systems is presented. It is shown that the sufficienta prioriinformation required for adaptive stabilization is the order of a stabilizing regulator. This requirement can be further weakened if a more complicated controller is used.

ISSN:0020-7179    

DOI:10.1080/00207179508921532

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

This paper considers the use of balanced realizations in the context of plant and controller order reduction. The emphasis is placed on reduced-order models obtained by residualizing the less controllable and observable states of a balanced realization. The residualized system, unlike a truncated system or an optimal Hankel-norm approximation, maintains the steady-state gain of the system. In addition, balanced residualization is seen to give good matching at low and medium frequencies. This is favourable with regards to both plant and controller reduction. The method is demonstrated on examples and detailed comparisons made with balanced truncation and optimal Hankel-norm approximation. The importance of DC-gain matching and scaling in different set-ups is highlighted. Ways of reducing the 2-DOF (degree of freedom)H∞controller of Hoyleel al.(1991) are discussed and important conclusions drawn. A new proof of the error bound for balanced residualization is given in an appendix.

ISSN:0020-7179    

DOI:10.1080/00207179508921533

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

Least-squares optimal prediction, minimum variance control and generalized minimum variance control algorithms for a two-dimensional CARMA process are developed. Each algorithm involves the algebraic solution of a two-dimensional diophantine equation, and may be embedded within ‘classical’ two-dimensional systems theory. We show how the algorithms must be modified for any practical implementation to take into account the edges of the data field. In this case we show how we may analyse the process using multivariable theory, and explore the linkages between multivariable representations and two-dimensional systems.

ISSN:0020-7179    

DOI:10.1080/00207179508921534

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

The paper considers the problem of stabilizing a non-linear plant by means of a qualitative controller [u(k)] = k([x(k)]) that has access only to the qualitative value [x(k)] of the system statex(k) and can only determine one of a set of qualitative values [u(k)] of the command inputu(k) Necessary and sufficient conditions for the existence of a stabilizing qualitative controller and a procedure for determining such a controller are given. These conditions and the design algorithm refer merely to a qualitative model of the system rather than the precise state-space description. The results are illustrated by a numerical example.

ISSN:0020-7179    

DOI:10.1080/00207179508921535

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

Prediction error learning algorithms for neural state space models are developed, both for the deterministic case and the stochastic case with measurement and process noise. For the stochastic case, a predictor with direct parametrization of the Kalman gain by a neural net architecture is proposed. Expressions for the gradients are derived by applying Narendra's sensitivity model approach. Finally a linear fractional transformation representation is given for neural state space models, which makes it possible to use these models, obtained from input/output measurements on a plant, in a standard robust performance control scheme.

ISSN:0020-7179    

DOI:10.1080/00207179508921536

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

We address the problem of practically stabilizing nonlinear and/or uncertain continuous-time dynamic systems when the norm of the control input is subject to a given fixed bound. We consider a class of systems whose nominal part is linear and whose nonlinear/uncertain part does not satisfy the matching condition. In this treatment no statistical information regarding the uncertainties is needed. Only a norm-bound on each nonlinear/uncertain quantity is assumed. We propose a bounded state-feedback controller whose design incorporates elements from both variable structure control theory and the deterministic control methodology. Using the second method of Lyapunov we obtain sliding domains, regions of uniform ultimate boundedness, and estimates of the domain of attraction for systems employing this controller. The closed-loop stability analysis as well as the design of the controller is facilitated by introducing a special coordinate transformation. The approach is illustrated by a numerical example.

ISSN:0020-7179    

DOI:10.1080/00207179508921537

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

This paper gives a workable method for practical stability study (with settling time) of nonlinear time-varying disturbed systems. Sufficient conditions are obtained by the use of vector norms, which allow estimation of initial, final, admissible subsets of state space, related to chosen settling time and final time. A numerical example is given to illustrate results.

ISSN:0020-7179    

DOI:10.1080/00207179508921538

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

Polynomial optimization has been applied to multivariabie control in the presence of stochastic inputs including coloured measurement noise. The method has been derived using the calculus of variations, which is thought to be a simpler formulation than completing squares. Both discrete-time and continuous-time systems are considered.

ISSN:0020-7179    

DOI:10.1080/00207179508921539

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor

摘要:

The idea of sliding mode control (SMC) as a robust control technique is utilized to control systems where the dynamics can be described byẋ(t) = (A + ΔA)x(t) + (B + ΔB)u(t) + d(t) where ΔA, ΔBandd(t) characterize unknown plant parameters and unexpected disturbances, respectively. The analysis is described in the discrete form using the Euler operator. The proposed controller regards the influence of unknown disturbances and parameter uncertainties as an equivalent disturbance and generates a control function (estimate) to cancel their influence by the mechanism of time delay, The states of the uncertain plant are steered from an arbitrary initial state to a stable surface,s = 0, and the plant output is subsequently regulated. One feature of the control is that the sliding conditions are satisfied without the discontinuous control action used in classical SMC. It therefore retains the positive features of SMC without the disadvantage of control chattering. The controller has been studied through simulations and experiment on an NSK direct drive robot arm driven by a DC motor. The results confirm that the control is robust to disturbances and parameter variations.

ISSN:0020-7179    

DOI:10.1080/00207179508921540

出版商:Taylor & Francis Group    

年代:1995

数据来源: Taylor