الفهرس | Only 14 pages are availabe for public view |
Abstract Industrial requests for increasing the mass production rates lead to the need for faster production machines that can produce, manipulate, or assemble parts at higher speeds and with acceptable accuracy than ever before. This brings the motivation for the research in this thesis, which has been to develop new control strategies that can achieve high performance for servomechanisms systems, and also, accommodate many disturbances in their motion delivery so that better tool positioning accuracy can be realized at high speeds. Detailed dynamic modeling and system identification has been derived, considering nonlinearity resources (friction and backlash). New intelligent controllers were designed with different techniques. The first methodology of these techniques is the fixed structure controllers such as the PID controller, the Fractional order PlO (FOPID) control and a new form of Non linear PID (NPID) control. The optimal values of the controller’s parameters were tl’btained using the Harmony Search (HS) optimization technique based on a suitable objective function. Still, the servomechanism system has poor performance in case of different operating points because of the fixed structure of controllers. So, this study resorts to the second methodology where the controller structure is variable. A new technique was developed to tune the FOPID control parameters online based on the optimal model reference adaptive system (MRAS). Also, this study presents a novel technique for variable structure (VS) fuzzy PO control where the rule base of the fuzzy system is tuned online according to optimal MRAS. A complete simulation for the advanced control techniques has been studied. The experimental setup has been implemented to verify the |