RLS Method Research Articles

Analisis Rasio 3 - Bank Komersial dengan Uji - Rls: Implikasi dan Bukti Kinerja Keuangan Bank Indonesia dan Malaysia

Abstracts This research aims to analyze the interaction between commercial banks in Indonesia and commercial banks in Malaysia on bank financial performance reports seen from the ratio aspect of bank financial reports. The method used in this research is a quantitative descriptive method by knowing the existence of the Dependent variable value on the variable (Independent) or more without making relationships and comparisons with other variables. In terms of bank value using the 3 - RLS implementation route, namely, the bank's Profitability Ratio is calculated by looking for Return on Assets (ROA), Return on Equity (ROE), Net Profit Margin (NPM), and Operating Expenses / Operating Income (BOPO). The Liquidity Ratio is calculated by finding the Quick Ratio (QR), Loan to Deposit Ratio (LDR), and Loan to Assets Ratio (LAR). The Solvency Ratio is calculated by looking for the Capital Adequacy Ratio (CAR) and Debt to Equity Ratio (DER). The results of this research evaluate and see the feasibility of 3 commercial banks in Indonesia and Malaysia against the Central Bank using the Triple - RLS method concept. As for commercial banks, there is policy integration with central bank criteria. Therefore, there needs to be discipline and commitment in improving financial performance in financial reports between Indonesian and Malaysian commercial banks.

Regularization of the RLS algorithm for adaptive digital predistortion

Problem statement. Modern digital pre-image input systems, as a rule, involve the use of adaptation algorithms to correct their parameters. Adaptation algorithms are solutions based on LMS and RLS methods. At the same time, the efficiency, in terms of the convergence rate and the accuracy of the solution, of RLS methods is significantly higher. This is due to the presence of a covariance matrix as part of the solution based on the RLS method. However, when using RLS algorithms (an adaptation algorithm using the RLS method), problems may arise related to poor conditionality of the covariance matrix resulting from signal noise, high inertia of the nonlinear properties of the power amplifier, limited accuracy of parameter calculation, etc. To solve this problem, it is advisable to use the regularization procedure of the RLS algorithm, taking into account the specifics of the digital predistortion systems. Objective. Creation and analysis of the regularization procedure of the RLS algorithm for adaptive input systems of digital presets. Results. The paper presents the implementation of the regularization procedure of the RLS algorithm for adaptive input systems of digital presets. Using the regularization procedure of the RLS algorithm avoids the state of poor conditionality of the covariance matrix, thereby ensuring stable operation of the digital pre-order input system. The state of the covariance matrix is monitored at each iteration of the RLS algorithm by evaluating the trace of the matrix. Practical importance. The proposed solution can be used to stabilize the parameters of adaptive systems for entering pre-orders based on RLS algorithms.

Research on parameter identification of shaking table systems based on the RLS method.

It is difficult to accurately establish a model of the real mesa system. Furthermore, a model of a seismic simulation vibration table array system is critical to increasing the accuracy of seismic testing in laboratory settings. Herein a model of the nine subarray shaking table system is identified by recursive extension of the least square method, which is used to accurately identify the structure parameters by simulation of the structure assuming a single degree-of-freedom. Then, through the displacement of the empty shaking table and the application of the recursive least squares algorithm, the model of the seismic simulation vibration table array is established. Through this study, the vibration table model of different construction forms can be obtained, and the parameters that are difficult to measure for some complex structures can effectively be determined.

A study on Bayesian method for reliability evaluation of small sample size aviation support systems

In order to realize the reliability evaluation of small sample size aviation support system with known prior information, the Bayes methods of system reliability evaluation are given by using the second-order moment equivalent method, relative least squares method (RLS method), maximum entropy method (ME method) and Chebyshev polynomial method respectively, and the accuracies of the above Bayes synthesis methods are compared and analysed through an example. The results show that the ME method and RLS method have higher evaluation accuracy than the second-order moment equivalent method and Chebyshev expansion method. Finally, ME method and RLS method are applied to the reliability evaluation of aviation support system, and good evaluation results are obtained. At the same time, it provides a valuable reference for the reliability evaluation of complex system with small sample size in engineering practice.

Retrospection of Nonlinear Adaptive Algorithm-Based Intelligent Plane Image Interaction System.

This paper introduces the application and classification of an adaptive filtering algorithm in the image enhancement algorithm. And the filtering noise reduction impact is compared using MATLAB software for programming, image processing, LMS algorithm, RLS algorithm, histogram equalisation algorithm, and Wiener filtering method filtering noise reduction effect. To optimize the intelligent graphic image interaction system, the proposed nonlinear adaptive algorithm of intelligent graphic image interaction system research is based on the digital filter and adaptive filtering algorithm for simulation experiment. The experimental results of several noise index data filtering algorithms show that the fuzzy coefficient k of LMS index is 0.86, RLS index is 0.91, the histogram equalization index is 0.53, and the Wiener filtering index is 0.62. LMS index of quality index Q is 0.90, RLS index is 0.95, histogram equalization index is 0.58, Wiener filtering index is 0.65. According to the above results, comparing LMS with the RLS method and according to SNR, k, and Q values in the simulation results in the process of processing, it is found that the convergence speed of the RLS algorithm is obviously better than that of the LMS algorithm, and the stability is also good. Additionally, the differential imaging data can provide a strong reference for the clinical diagnosis and qualitative differentiation of TBP and CP, and MSCT is worthy of extensive application in the clinical diagnosis of peritonitis. The processing effect of the image with high similarity to the original image is greatly improved compared with the histogram equalization and Wiener filtering methods used in the simulation.

Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System

In this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking oscillations into account that occur in the system and minimizing their impact on the overall system performance. Parameters of models used by the controller are obtained on the basis of the introduced black-box models both for a turbine and a synchronous generator, parameters of which are estimated in an on line fashion using a RLS method. The aim of this paper is to compare the behavior of the classical generator control system with a power system stabilizer and a model predictive control with an additional feedback signal. The novelty of the paper is related to the use of the predictive controller instead of the classical controller/stabilizer system and its possibility of stabilizing the power system. Contrary to the solutions found in the literature, which are commonly-based on a fuzzy logic approach, the authors propose the use of an adaptive model predictive controller, which takes advantage of the knowledge concerning the plant in the form of a model and adapts itself to the operating point of the system using the model parameters estimation mechanism. Moreover, the adaptive predictive controller, unlike other solutions, automatically adjusts signal levels to changes in the plant. The proposed solution is able to calculate the best control signal regardless of whether these changes of the plant are caused by a change in the operating point, or resulting from operation, e.g., wear of mechanical parts.

Two-dimensional incremental recursive least squares identification for batch processes

In this paper, two-dimensional incremental recursive least squares identification methods for batch processes are proposed. First, parameter increment along the time direction is introduced to represent the batch process, which changes slowly along the batch direction in comparison with the parameters. Then, we apply RLS method along the batch direction to derive two kinds of two-dimensional incremental recursive identification algorithm, which can use the latest estimation results along both the time direction and batch direction to obtain the new estimated value. By extending the model assumption from parameter batch-invariant to parameter increment batch-invariant, this method can effectively accelerate the convergence rate. Furthermore, the convergence property of the proposed method is established by the associated ordinary differential equation method. Finally, we demonstrate the superiority of the proposed identification method in two case studies.

Reweighted Error Reducing Channel Estimator for QoS Enhancement in Wireless Nautical Radio Networks

Maritime explorations may suffer from unwanted situations such as delays, insecurity, congestions, and collisions, etc., which may arise from severe environmental conditions. Thus, there is a need to develop proper techniques that will improve the overall quality of service (QoS) of marine users. This work aims to address the limitations of wireless transmissions over maritime communication systems using channel estimation (CE) by designing and verifying the performances of two estimators named inter-symbol interference/average noise reduction (ISI/ANR) and reweighted error-reducing (RER) for aggrandizing the quality of nautical radio transmissions. To show that adopting accurate and stable CE methods can considerably increase the QoS requirements of marine networks, the performances of the proposed estimators are analysed in comparison to traditional methods under signal propagations assuming both line of sight (Rician) and Non-line of sight (Rayleigh) conditions. The adoption of a reweighting attractor in addition to the introduction of a variable leakage factor controlled log-sum penalty function to our proposed RER estimator provides additional stability for the estimation of oceanographic channels. Results obtained highlight that the proposed estimator demonstrates a performance gain of over 1 dB at a data rate of 100 bps under severe fading environments in comparison to the customary RLS technique. At an MSE of 10−2, the RER method under slow fading channels show a performance gain of about 1 dB when compared to the traditional RLS method while similarly showing superiority gain of about 0.6 dB over RLS method assuming fast fading Rayleigh channel conditions.

Electrical Equivalent Circuit of Multi-Tips Pulsed Corona Discharge Reactor

In this work, an electrical model equivalent to the corona discharge reactor has been proposed in a multitips plan configuration, in dry air at atmospheric pressure. The electrical parameters evolution of the circuit are obtained by using the identification method which is based on the least squares recursive (RLS) algorithm, the estimated parameters allow us to describe the corona discharge behavior inside the reactor. The RLS method used during the determination of capacitance and resistance is validated by the comparison between the measured and the calculated currents, the significant forms of capacitance and resistance confirm the validity of the proposed electrical model. The estimated parameters of the electrical circuit allowed us to determine the discharge power, the power delivered to the reactor and thus the energy efficiency during the discharge, this efficiency increases during the propagation of streamers towards the plane, it reaches a maximum value which is equal to 50% in the case of the fourtips- plane configuration. The energy stored in the reactor is also calculated using the electrical circuit, it increases to a maximum value of 2.6 pJ, which is a very low value compared to the energy delivered to the reactor. This work allows us to control the discharge and lost energy during the corona discharge in the case of multi-tips-plane configuration.

Recursive least squares based sliding mode approach for position control of DC motors with self-tuning rule

In this paper, a self-tuning rule-based position control algorithm is proposed for DC motors with system parameter estimation using the recursive least squares method. First, a mathematical model of the angular position control of a DC motor was derived. Next, the time-varying parameters including the rotational inertia in the model were estimated using the RLS method along with multiple forgetting factors without prior knowledge of the system. Based on the derived model and the parameter estimation, a sliding mode control algorithm was designed by applying a self-tuning rule that enables the magnitude of the voltage input to be adaptively adjusted for improvement of the energy efficiency. The performance of the designed control algorithm was then experimentally evaluated under several different load conditions. Finally, the evaluation results show that the designed controller achieves a satisfactory capability for a DC motor to deal with both tracking accuracy and energy efficiency without prior knowledge of the system.

Design of Efficient Power Filter with Reduced Distortion Using Control Algorithm

The electrical distribution system is facing undesirable power quality disturbances due to different types of linear/nonlinear loads on the supply system. The objective of the project is to reduce the distortion level in voltage or current input to the load and at the output of the filter. To design a simple but highly viable hybrid active power buffer that is capable of feeding less distorted voltage to the nonlinear load model. To present an optimal controlling of these buffers so as to minimize the voltage distortion by designing a different algorithm for the same. Comparing the THD levels of the output voltage waveform with the standard controlling method with the proposed control design to further enhance the proposed design such that it is practically feasible to be implemented in grid system having renewable energy resources. In this work, a power filter has been designed using different algorithms with an objective to reduce the Total Harmonic Distortion in the voltage output waveforms. The total harmonic distortion in the voltage output waveform being fed to the load using only the PQ_RLS algorithm is found to be 2.18 %. In the case of the output voltage from the power buffer using PQ_RLS algorithm, the THD level is 0.17 %. The distortion level in the output voltage waveforms in both the cases being fed to the load when compared, it is found that RLS algorithm in combination with PQ algorithm is more effective in reducing the distortion as compared to standard RLS method or PQ method.

Rapid determination of trace potassium in drinks and serum by Rayleigh light scattering technique

In this paper, a sensitive, rapid and selective method based on Rayleigh light scattering technique (RLS) was proposed for the determination of potassium using a conventional spectrofluorometer. Potassium was transformed to KB(C6H5)4 particles, which displayed intense light scattering in aqueous solutions. Effects of factors such as wavelength, acidity, ionic strength and coexistent interferents on the RLS of B(C6H5)4-K were investigated. The RLS intensity of the KB(C6H5)4 suspension was obtained in NaAc solution (0.50 M, pH = 8.0) and the addition of 0.5 mL of sodium dodecyl benzene sulfonate (5.05 μM) and 1.0 mL of tetraphenylborion sodium (1.0%). The Rayleigh scattering light intensity at the maximum peak of 567 nm was proportional to the concentration of potassium ion in the range of 0.20-1.60 μg mL-1 with a detection limit of 0.10 μg mL-1. To determine the feasibility of the proposed method, samples of water, drinks and serum were analyzed. The attained results were in agreement with the ion-selective electrode method. Good recovery was also obtained in a range of 95.10-107.02%. The sensitivity and selectivity of the RLS method are high enough to determine trace amounts of potassium ion without any significant interference from high levels of other components such as common anions and cations.

Experimental Verification of a Novel Quad-RLS Technique for Improving Real-time System Identification Performance: A Practical Approach to CMG

This paper presents a Quad RLS(Q-RLS) technique with four RLSs under a fixed forgetting factor condition to improve the identification performance of a dynamical system in a real-time fashion. Although an adaptive RLS method with a variable forgetting factor and a higher order model may provide the modeling accuracy, their implementations are not easy because of leakage effects and relatively complex modeling. In practice, the fixed forgetting factor is still used for the RLS-based system identification. Therefore, a novel Q-RLS scheme with concurrent four RLSs is proposed as an alternative way for the better estimation performance in an on-line fashion. In the Q-RLS scheme, the first pair of the forward and inverse RLSs is to identify the forward and inverse models independently. The second pair of the forward and inverse RLSs is to improve the identification of the previously identified model. The proposed approach has several advantages: 1) The RLS with a fixed forgetting factor can avoid the leakage problem. 2) Both forward and inverse models are separately identified to improve the accuracy. 3) Q-RLS can have the 4th order filter structure, but provide the better identification performance. Three schemes such as a second-order RLS, a fourth-order RLS, and the Q-RLS are experimentally tested and their performances are compared for the state observation accuracy of the control moment gyroscope(CMG) system.

Comparison of LQG and Adaptive PID Controller for USV Heading Control

This paper considers USV heading controller using Adaptive PID and LQG controller. PID is a conventional controller and the most industry controller. However, PID parameters are selected by trial and error. That problem proposed Adaptive PID how to tune PID parameters. In this paper, PID parameters are estimated by RLS method. The second controller for comparison is LQG. LQG controller is robust controller. A gain regulator estimation method, Kalman Filter, is used as LQG controller. The computational results show the LQG controller has better performance than Adaptive PID.

Heading angle and depth control of micro-ROVs using adaptive minimum-degree pole placement (MDPP) approach

Underwater vehicles are known as complex systems with extremely nonlinear nature, and it makes them hard to control and steer. Due to uncertainty in model, strong disturbances cause by water streams, etc. Control of such devices is a hard task to accomplish in providing a precise mathematical model of a dynamic system that is the most important step in analysis and design of an autopilot. In present study, a ROV which its motion can be described in 3D space with six degrees of freedom has been considered. In spite of a great level of complexity caused by hydrodynamic forces and moments which have a highly nonlinear nature, a precise mathematical model of DST-R-100-4 with all effects of hydrodynamics terms, added mass, buoyancy forces and so on has developed. The model equations and parameters are extracted from related references. Considering the variation of system’s parameters and lack of knowledge about the variation ranges of them, an adaptive pole placement strategy is employed in order to control and achieve an acceptable performance. For this reason, online identification based on RLS method is realized and model parameters can be updated in each sampling time. To investigate the performance of the controller, simulations are performed in presence of variant parameters of the dynamic model and external disturbances. Results show a suitable performance for the designed controller.

An improved collaborative representation based classification with regularized least square (CRC–RLS) method for robust face recognition

Fast and robust face recognition is a challenging research topic in the field of computer vision. A recently proposed Collaborative Representation based Classification with Regularized Least Square (CRC–RLS) algorithm shows very lower computational cost but with poor robustness. In order to solve this problem, we propose an improved CRC–RLS method. Firstly, the image Gabor features were extracted and used to construct initial dictionary. Secondly, we learn a discriminative dictionary by a label consistent K-SVD (LC-KSVD) method which combines the sparse coding error with the reconstruction error and the classification error. Finally, l2-norm of coding residual in CRC–RLS is computed and the classification problem is transformed into solving linear programing problem. Experiments on two benchmark face databases with variations of illumination, expression, occlusion show that the proposed method can achieve high classification accuracy and has a very low time-consuming.

Recursive maximum likelihood method for the identification of Hammerstein ARMAX system

Identification of Hammerstein nonlinear models has received much attention due to its ability to describe a wide variety of nonlinear systems. This paper considers the parameter estimation problem of ARMAX models for the Hammerstein systems. The recursive maximum likelihood method, which can be applied to online identification and occupies small memory capacity, is proposed to deal with the problem in here. It is an approximation of the maximum likelihood method. The parameters of the linear and nonlinear parts of the Hammerstein model and the noise model can be directly obtained without using the overparameterization technique. Finally, the proposed method is applied to a classic Hammerstein ARMAX system and is compared with RLS method in detail. The research results show the effectiveness of the proposed method.

Positioning performance analysis using RWLS algorithm based on variance estimation methods

GPS is a navigation system that allows users to calculate their position in every desirable point on earth, sea or air as well as space. By increasing the velocity of receiver, the positioning accuracy will decrease; while it is very important to calculate the position of high velocity moving objects such as planes or ultra-high velocity moving objects like satellites. In this paper, seven methods for dynamic positioning, using recursive least squares method with pseudo-range and carrier phase measurements combined with the variance estimation methods for weighting observations are presented. Simulation results on data with different velocities from 100 m/s to 7300 m/s show that proposed methods reduce the positioning errors at high velocities by more than 50% compared to the RLS method.

Self-Tuning Predictive PID Controller Using a Time-Varying Proportional Gain

This paper proposes a new design method of adaptive GPC-based PID controller. The proportional gain of a PID controller is time-varying, and the PID controller is designed based on strongly stable GPC that is extended by using coprime factorization. Hence, a GPC law can be approximated by the PID controller finely. Finally, the system parameters are updated in real-time to resist to disturbance, by using the RLS method. Simulation examples show the effectiveness of the proposed method.

Resonance light scattering for detecting fluoride ions based on the formation of a uranyl coordination supramolecular polymer

Illustrated procedure of detecting fluoride ions by the RLS method.