| نویسندگان | مرضیه احمدی,علیرضا فرجی ارمکی |
| نشریه | نشریه مهندسی و مدیریت انرژی دانشگاه کاشان |
| شماره صفحات | 2 |
| شماره مجلد | 11 |
| ضریب تاثیر (IF) | ثبت نشده |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2021-12-31 |
| رتبه نشریه | علمی - پژوهشی |
| نوع نشریه | الکترونیکی |
| کشور محل چاپ | ایران |
| نمایه نشریه | ISC |
چکیده مقاله
This paper designs an Optimized Adaptive Combined Hierarchical Sliding Mode Controller (OACHSMC) for a timevarying crane model in presence of uncertainties. Uncertainties have always been one of the most important challenges
in designing control systems, which include unknown parameters or un-modeled dynamics in systems. Sliding mode
controller (SMC) is able to compensate the system in the presence of uncertainties due to un-modeled dynamics and is
used for robust stability and performance behavior in the presence of additive un-modeled dynamics of system and
multiplicative friction forces. This under-actuated crane has two sub-systems: trolley and payload. Therefore, it can be
controlled by a single input signal with combined hierarchical sliding mode controller (CHSMC) using a two-layersliding manifold accurately. Payload mass and cable length are time-variant variables through load transferring. Due to
the Time-varying models and the inefficiency of most controllers, the use of an adaptive controller can help improve
system performance. This controller is adapted by considering a time-varying coefficient of the second layer sliding
manifold. For energy saving of the input signal, the parameter of the first layer sliding manifold of ACHSMC is
optimized by two intelligent strategies: genetic algorithm (GA) and particle swarm optimization (PSO) method. The
simulation results show robust stability and performance of the proposed optimized controller.