Search results for "Stiction"
showing 3 items of 3 documents
Stick-slip and convergence of feedback-controlled systems with Coulomb friction
2020
An analysis of stick-slip behavior and convergence of trajectories in the feedback-controlled motion systems with discontinuous Coulomb friction is provided. A closed-form parameter-dependent stiction region, around an invariant equilibrium set, is proved to be always reachable and globally attractive. It is shown that only asymptotic convergence can be achieved, with at least one but mostly an infinite number of consecutive stick-slip cycles, independent of the initial conditions. Theoretical developments are supported by a number of numerical results with dedicated convergence examples.
Model Identification using a Statistical Cluster LPC approach with Application to Motion of a Brushless Motor
2006
This paper presents a new statistical method based on Cluster Last Principal Component (CLPC) algorithm to identify nonlinear, time-varying, dynamical models from input-output data clusters of black boxes. Each of data clusters is on a time window. For every data cluster an appraiser updates the parameters of a Gaussian time-varying model via an optimality design criterion that maximises the Likelihood function and the estimated steady-state parameters of this model are quasi-constant values. An application to identify the nonlinear model of a control system of a brushless motor is developed. By applying of CLPC algorithm to this system, the actual angular positions of the brushless motor a…
Manipulator Control System Model Estimation Unsing a Real Time Finite State Machine based on Statistical LPC Analysis
2005
This paper presents a new statistical method based on a real-time Last Principal Component (LPC) algorithm to estimate single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) varying time dynamical models from input output data clusters of non stationary black boxes. Each of data clusters is on a time window. A real time estimation algorithm via statistical LPC algorithm and an appraiser called "finite state machine" is then described. For every data cluster the finite state machine updates the parameters of a Gaussian varying time model via an optimality design criterion that maximises the Likelihood function. Using the LPC algorithm and the finite state machine, the es…