Anti-Swing Control For An Overhead Crane With Fuzzy Compensation

Abstract

This paper proposes a novel anti-swing control strategy for an overhead crane. The controller includes both position regulation and anti-swing control. Since the crane model is not exactly known, fuzzy rules are used to compensate friction, gravity as well as the coupling between position and anti-swing control. A high-gain observer is introduced to estimate the joint velocities to realize PD control. Real-time experiments are presented comparing this new stable anti-swing PID control strategy with regular crane controllers.

Underactuated robotics: A review

“…Fuzzy control Model-based fuzzy control [154][155][156][157][158][159][234][235][236] Model-free fuzzy control [160][161][162]164,[166][167][168][169][170][237][238][239] Hybrid fuzzy control [171][172][173][174] The integration of fuzzy control with other traditional control Fuzzy PID composite control [175][176][177][178][179][180][181][182][240][241][242] Sliding mode variable structure control 205, Backstepping control 186,[276][277][278][279] Adaptive fuzzy control 127,189,190,[280][281][282]…”

An optimal performance control scheme for a 3D crane

“…They are easy to implement, low cost and effective and thus they have a significant role in industrial applications. Many type of PID based control schemes to control the swing motion and cart position of the cranes have been presented by researchers including neural network based PID controller [15], PSO based PID controllers [16], genetic algorithm based PID controllers [17] and fuzzy based PID controllers [18][19][20]. Combination of input shaping and PID controller has been previously proposed [21].…”

Fuzzy logic-based adaptive control system prototypying for laboratory scaled overhead crane

“…Furthermore, the soft computing techniques, especially fuzzy logic, are widely employed to the considered problem. The linguistic-rule-based fuzzy controllers are reported in [10][11][12][13], as well as proposed for PID gains tuning [14,15], or sliding mode control [16]. TSK-type fuzzy controllers are proposed for example in [17,18].…”