Abstract
The paper focuses on multivariable generalized predictive control (GPC) of an underactuated overhead crane with constraints on manipulated variable and sway angle of a payload. The adaptive control scheme is developed based on the discrete-time linear parameter varying model of a crane dynamic identified using the recursive least square (RLS) algorithm with parameter projection. Particle swarm optimization (PSO) is applied to solve the optimization control problem subject to hard constraint on control signal and the soft constraint payload deflection in the transient state. The feasibility and applicability of the proposed control approach is confirmed using a laboratory scaled overhead crane for different constraint and operating conditions.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
