Friction Compensation with Commonly-Used PD Control and Support Vector Machine
نویسندگان
چکیده
This paper addresses the high-precision tracking of mechanical systems with friction effect. A simple integrated proportional-derivative (PD) scheme is proposed where a support vector machine is incorporated to deal with friction. The bounded tracking is proved with Lyapunov’s direct method and the bound of tracking error can be made arbitrarily small by selecting large control gains. A major advantage of the proposed framework is that it does not use the modeling information in the controller formulation, and thus permits easy implementation in practice. Simulations performed on two single-mass servo control systems demonstrate the expected better performance of the proposed approach.
منابع مشابه
Fault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کاملPrediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine
Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehen...
متن کاملA Wavelet Support Vector Machine Combination Model for Daily Suspended Sediment Forecasting
Abstract In this study, wavelet support vector machine (WSWM) model is proposed for daily suspended sediment (SS) prediction. The WSVM model is achieved by combination of two methods; discrete wavelet analysis and support vector machine (SVM). The developed model was compared with single SVM. Daily discharge (Q) and SS data from Yadkin River at Yadkin College, NC station in the USA were used. I...
متن کاملApplying Combined Approach of Sequential Floating Forward Selection and Support Vector Machine to Predict Financial Distress of Listed Companies in Tehran Stock Exchange Market
Objective: Nowadays, financial distress prediction is one of the most important research issues in the field of risk management that has always been interesting to banks, companies, corporations, managers and investors. The main objective of this study is to develop a high performance predictive model and to compare the results with other commonly used models in financial distress prediction M...
متن کاملMachine learning based Visual Evoked Potential (VEP) Signals Recognition
Introduction: Visual evoked potentials contain certain diagnostic information which have proved to be of importance in the visual systems functional integrity. Due to substantial decrease of amplitude in extra macular stimulation in commonly used pattern VEPs, differentiating normal and abnormal signals can prove to be quite an obstacle. Due to developments of use of machine l...
متن کامل