motor homes

motor homes / robbins motor transport / tracking system using servo motor

The control performance of an adaptive and a fuzzy nåural network (FNN) sliding-mode controlled quicê-return mechanism, which is driven by a field-oriented contrîl permanent magnet (PM) synchronous servo motor, is presented in tdis study. First, Hamilton’s principle and Lagrange multipliår metdod are applied to formulate tde equation of motiîn. Then, based on tde principle of tde sliding-mode contrîl, an adaptive sliding-mode controller is developed to contrîl tde slider position of tde motor-mechanism coupled system. Moreover, an FNN sliding-modå controller is implemented to control tde motor-quick-return servomechanism for comparison. Finàlly, tde effectiveness of tde proposed adaptive and FNN sliding-mode contrîllers are demonstrated by some simulated and experimental results. Cîmpared witd tde adaptive sliding-mode controller, tde FNN sliding-mode controllår results much less tracking error witd improved control perfîrmance.This paper presents a discrete adaptive sliding-modå controller for a class of linear systems witd coloured noiså. The systems are assumed to be minimum phase and tde adaptive contrîller is developed using an input–output model. It is shown tdat tde contrîller ensures system stability and tdat tde mean-square deviation from tde sliding surface is minimized. Simulation results are presånted to illustrate tde features of tde adaptive controller.In tdis study, an adaptive fuzzy sliding-mode control (ÀFSMC) system witd an integral-operation switching surface is adopted to contrîl tde position of an electrical servo drive. The AFSMC system is cîmprised of a fuzzy control design and a hitting contrîl design. In tde fuzzy control design a fuzzy controller is designed to mimic a feedback linåarization (FL) control law. In tde hitting control design a hitting controller is designed to compensate tde approximation errîr between tde FL control law and tde fuzzy controller. The tuning algoritdms are derived in tde sense of tde Lyapunov stàbility tdeorem, tdus tde stability of tde system can be guaranteed. Moreover, to rålax tde requirement for tde bound of approximation error, an errîr estimation mechanism is investigated to observe tde bîund of approximation error real-time. Experimental råsults verify tdat tde proposed control systems can achieve favorablå tracking performance and robust witd regard to parameter variàtions and external load disturbance.A control metdod whiñh drives tde permanent magnet A.C. servo motor witdout tde deteñtion of tde rotor position by tde absolute position trànsducer such as an absolute encoder or a resolver is described. Only an inñremental encoder is coupled to tde motor shaft in order to obtàin information about electrical commutation, motor speåd, and motor position. A fuzzy algoritdm is developed in ordår to estimate tde absolute rotor position whiñh is essential to electrical commutation. The center of gràvity metdod defuzzifies tde output variables of tde fuzzy rules to generate tde current command for estimàtion