Recursive identification of time-varying non-linear cascade systems with static input and dynamic output non-linearities

The paper deals with the recursive identification of time-varying non-linear dynamic systems using three-block cascade models with non-linear static, linear dynamic and non-linear dynamic blocks. These models are appropriate for systems with both actuator and sensor non-linearities. Multiple application of a decomposition technique provides special expressions for the corresponding non-linear model description that are linear in parameters. A modified recursive least-squares-based algorithm is used for estimation of the time-varying input polynomial and output backlash parameters. Simulation studies show the feasibility of proposed approach to estimate the model parameters and track their changes.

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Identification of Nonlinear Cascade Systems with Time-Varying Backlash

Journal of Electrical Engineering ◽

10.2478/v10187-011-0014-2 ◽

2011 ◽

Vol 62 (2) ◽

pp. 87-92 ◽

Cited By ~ 12

Author(s):

Jozef Vörös

Keyword(s):

Linear Problem ◽

Least Squares Method ◽

Analytic Form ◽

Internal Variable ◽

Recursive Least Squares ◽

Recursive Identification ◽

Time Varying ◽

Simulation Studies ◽

Cascade Systems ◽

Recursive Least Squares Method

Identification of Nonlinear Cascade Systems with Time-Varying BacklashRecursive identification of cascade systems with time-varying input backlash and linear dynamic system is presented. A new analytic form of backlash characteristic description is used, hence all the parameters in the cascade model equation are separated and their estimation is solved as a quasi-linear problem using the recursive least squares method with internal variable estimation. Simulation studies are included.

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Adaptive control of time-varying non-linear plants by speed-gradient algorithms

Information and Control Systems ◽

10.31799/1684-8853-2019-3-37-44 ◽

2019 ◽

pp. 37-44 ◽

Cited By ~ 1

Author(s):

O. P. Tomchina ◽

D. N. Polyakhov ◽

O. I. Tokareva ◽

A. L. Fradkov

Keyword(s):

Adaptive Control ◽

Adaptive Systems ◽

Reference Model ◽

Maximum Deviation ◽

Model Parameters ◽

Time Varying ◽

System Solution ◽

Non Linear ◽

Initial Uncertainty ◽

Speed Gradient

Introduction: The motion of many real world systems is described by essentially non-linear and non-stationary models. A number of approaches to the control of such plants are based on constructing an internal model of non-stationarity. However, the non-stationarity model parameters can vary widely, leading to more errors. It is only assumed in this paper that the change rate of the object parameters is limited, while the initial uncertainty can be quite large.Purpose: Analysis of adaptive control algorithms for non-linear and time-varying systems with an explicit reference model, synthesized by the speed gradient method.Results: An estimate was obtained for the maximum deviation of a closed-loop system solution from the reference model solution. It is shown that with sufficiently slow changes in the parameters and a small initial uncertainty, the limit error in the system can be made arbitrarily small. Systems designed by the direct approach and systems based on the identification approach are both considered. The procedures for the synthesis of an adaptive regulator and analysis of the synthesized system are illustrated by an example.Practical relevance: The obtained results allow us to build and analyze a broad class of adaptive systems with reference models under non-stationary conditions.

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