Time optimal control of overhead cranes with hoisting of the load
Automatica (Journal of IFAC)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Adaptive Neural Network Control of Robotic Manipulators
Adaptive Neural Network Control of Robotic Manipulators
Principles of Neurocomputing for Science and Engineering
Principles of Neurocomputing for Science and Engineering
Design of Feedback Control Systems
Design of Feedback Control Systems
Control of overhead cranes using a fuzzy logic controller
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Adaptive neural network control of nonlinear systems by state andoutput feedback
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling, identification, and control of a class of nonlinear systems
IEEE Transactions on Fuzzy Systems
Adaptive neural control of uncertain MIMO nonlinear systems
IEEE Transactions on Neural Networks
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Sensor is an indispensable component in feedback control. In anti-swing feedback control of automatic gantry crane system, sensors are normally employed to detect trolley position and payload swing angle. However, sensing the payload motion of a real gantry crane, in particular, is troublesome and often costly since there is hoisting mechanism on parallel flexible cable. Therefore, sensorless anti-swing control method for automatic gantry crane system is proposed in this study. The anti-swing control is performed in feedback control scheme without using real swing angle sensor. Instead, soft sensor approach is used to substitute the real swing angle sensor. The soft sensor is designed based on Dynamic Recurrent Neural Network (DRNN) as a state estimator. Thus, a DRNN is trained using input-output data to estimate payload swing angle from trolley acceleration and input voltage of trolley actuator. An experimental study using lab-scale automatic gantry crane is carried out to evaluate the effectiveness of the proposed sensorless anti-swing control. The results show that the proposed sensorless method is effective for payload swing suppression since similar performance to the sensor-based feedback anti-swing control is obtained.