This paper presents a model-reference adaptive control approach for systems with unstructured uncertainty based on two least-squares parameter estimation methods: gradient-based method and recursive leastsquares method. The unstructured uncertainty is approximated by Chebyshev orthogonal polynomial basis functions. The use of orthogonal basis functions improves the function approximation signif...

One kind of the colored noise interference systems is generalized output error model (OEARMA). This paper presents a two-stage recursive least squares algorithm for OEARMA. Aiming at the OEARMA, this paper puts forward a two-stage recursive least squares algorithm. The basic idea of the algorithm is to combinie the auxiliary model identification idea and the decomposition technique to decompose...

This paper proposes an online type of controller parameter tuning method by modifying the standard fictitious reference iterative tuning method and by utilizing the so-called recursive least-squares (RLS) algorithm, which can cope with variation of plant characteristics adaptively. As used in many applications, the RLS algorithm with a forgetting factor is also applied to give more weight to mo...

This note presents the basic recursive least squares (RLS) algorithm for recursively estimating parameters in linear regression models. In order to track time varying parameters a forgetting factor and a Kalman filter method are described. These methods may be used in some of the extra tasks in the project and is also used in the compulsory computer exercise (beräkningslaboration) No 5 . This n...

|This paper presents a new method for identiica-tion of fast-fading mobile channels (for which combinations of vehicle speed and carrier frequency give rise to signii-cant fading). Our new algorithm estimates both the channel statistics and the time-varying channel impulse response on-line. Simulation studies demonstrate the performance of the new estimator which couples an augmented Kalman l-t...

The recursive least squares (RLS) algorithm is well known and has been widely used for many years. Most analyses of RLS have assumed statistical properties of the data or the noise process, but recent robust H∞ analyses have been used to bound the ratio of the performance of the algorithm to the total noise. In this paper, we provide an additive analysis bounding the difference between performa...

Inter-symbol interference if not taken care off may cause severe error at the receiver and the detection of signal becomes difficult. An adaptive equalizer employing Recursive Least Squares algorithm can be a good compensation for the ISI problem. In this paper performance of communication link in presence of Least Mean Square and Recursive Least Squares equalizer algorithm is analyzed. A Model...

A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between inand output can he approximated, even when the structure of this relation is unknown beforehand. This method can adapt its structure on-line while it preserves information offered by previous samples, making it applicable in a control setting. This method has b...

We examine the problem of discrete time system estimation while not ignoring the underlying continuous time system. This leads to the use of a new discrete time operator , the operator, which approximates the continuous time derivative operator d dt. We use this to formulate system estimation algorithms, and discuss their signiicantly superior numerical properties when compared to the equivalen...

In this paper, a clustering-based method is proposed for automatically constructing a multi-input TakagiSugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to prov...