Optimal control of overhead cranes
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Cited by (97)
Fast or Cheap: Time and Energy Optimal Control of Ship-to-Shore Cranes
2023, IFAC-PapersOnLineModeling and control of overhead cranes: A tutorial overview and perspectives
2023, Annual Reviews in ControlOnline reinforcement learning with passivity-based stabilizing term for real time overhead crane control without knowledge of the system model
2022, Control Engineering PracticeCitation Excerpt :As a result, the development of high-performance automatic control system for overhead cranes is always of main concern for engineers and researchers. Beginning with time-optimal controllers designed in Auernig and Troger (1987) and Beeston (1969), numerous control methodologies for overhead crane systems have been presented in the literature, including but not limited to input shaping (Tho, Kaneshige, & Terashima, 2020), optimal control (Al-Garni, Moustafa, & Nizami, 1995; Hao, Hao, Zhang, et al., 2020; Oh, Seo, & Han, 2016), passivity-based control (Fang, Zergeroglu, Dixon, et al., 2001; Shen, Schatz, & Caverly, 2021; Sun & Fang, 2012), adaptive control (Yang & Shen, 2011) and robust control (Cheng & Chen, 1996). Most of the abovementioned work can be characterized as model-based control, in which the accurate mathematical model of the crane system serves as the foundation of the control synthesis.
A crane-based five-axis manipulator for antenna tests
2019, Control Engineering PracticeCitation Excerpt :Based on this model they present an Input Shaping control procedure that can be designed for overhead cranes (Peng, Singhose, & Frakes, 2012) or rotary cranes (Uchiyama, Ouyang, & Sano, 2013) in a similar way and that is based on the eigenfrequencies of the linearized system. Control approaches including feedback use the nearly decoupled behavior of overhead cranes and implement individual controllers for each axis based on Fuzzy techniques (Omar, Karray, Basir, & Yu, 2004; Yu, Moreno-Armendariz, & Rodriguez, 2011), PID control (Maghsoudi, Mohamed, Husain, & Tokhi, 2016; Solihin, Martono, Legowo, & Akmeliawati, 2009; Sun, Fang, Chen, & He, 2015), optimization (Al-Garni, Moustafa, & S.Nizami, 1995), or based on the root locus analysis of the transfer function (Lee, 1998). An approach that considers the full nonlinear model equations makes use of the flatness property of the load position of an overhead crane (Knierim, Krieger, & Sawodny, 2010) or the rather important coupling of a boom crane (Neupert, Arnold, Schneider, & Sawodny, 2010).
A switched optimal control approach to reduce transferring time, energy consumption, and residual vibration of payload's skew rotation in crane systems
2019, Control Engineering PracticeCitation Excerpt :Therefore, a numerical method will be adopted in this paper. In the domain of numerical approaches to solve a constrained optimal control problem, direct (Al-Garni, Moustafa, & Nizami, 1995; Becerra, 2004; Snyman, Frangos, & Yavin, 1992) and indirect (Lasdon, 1970; Lasdon, Mitter, & Waren, 1967; Quintana & Davison, 1974) methods can be found in the literature. However, the indirect techniques always result in a faster convergence rate and better cost performance index (Betts, 2009; Rao, 2009), thus it will be employed in this paper.
Fuzzy sliding mode control of an offshore container crane
2017, Ocean EngineeringCitation Excerpt :From the crane control aspect, various control algorithms have been proposed to deal with sway suppression. These methods include open-loop control, such as input shaping control for gantry cranes, bridges (Ngo et al., 2012; Hong et al., 2003; Huey et al., 2008; Robertson and Singhose, 2009; Singhose et al., 2000; Sorensen et al., 2007; Sorensen and Singhose, 2008; Sung and Singhose, 2009a, 2009b), and flexible systems in general (Hong et al., 2003; Huey et al., 2008; Robertson and Singhose, 2009; Singhose et al., 2000; Sorensen et al., 2007; Sorensen and Singhose, 2008; Sung and Singhose, 2009a, 2009b) as well as closed-loop control, such as optimal control (Al-Garni et al., 1995; Hong et al., 2000), state feedback control (Kim et al., 2004; Kłosiński, 2005; Messineo et al., 2008; Park et al., 2007; Sawodny et al., 2002), fuzzy control (Ahmad, 2009; Benhidjeb and Gissinger, 1995; Chang and Chiang, 2008; Chen et al., 2009; Cho and Lee, 2002; Omar et al., 2004), adaptive control (Cheng-Yuan, 2007; Liu et al., 2005; Messineo and Serrani, 2009; Mizumoto et al., 2007; Ngo and Hong, 2012a; Tuan et al., 2013; Yang and Yang, 2007), and robust control (Almutairi and Zribi, 2009; Bartolini et al., 2002a, 2002b; Lee, 2004a, 2004b, 2005; Lee et al., 2006; Ngo and Hong, 2012b; Orbisaglia et al., 2008; Xi and Hesketh, 2010). The conventional control methods developed for offshore container cranes may be unsuitable to mobile harbor cranes due to the effect of sea-excited motions (Ngo and Hong, 2012b).