Hybrid input shaping and fuzzy logic‐based position and oscillation control of tower crane system

Author:

Alhassan Ahmad Bala1,Assawinchaichote Wudhichai1ORCID,Zhang Huiyan2ORCID,Shi Yan3

Affiliation:

1. Department of Electronic and Telecommunication Engineering Faculty of Engineering, King Mongkut's University of Technology Thonburi Bangkok Thailand

2. National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing China

3. Graduate School of Science and Technology Tokai University Kumamoto Japan

Abstract

AbstractEffective control of the tower crane system (TCS) is crucial for the safe and quick transport of goods from one point to another in industries and construction sites. However, the existing literature either depends on the dynamic model of the system, which is prone to errors and assumptions, or requires the feedback of the states to be controlled, which can be costly and or complex. In particular, the TCS has many states and is highly nonlinear. Thus, a non‐model‐based control approach that depends on minimal feedback sensors is needed. The primary contribution of this work is that the potential hybrid configurations of the input shaping control (ISC) and fuzzy logic control (FLC) were proposed and investigated. The study provides the best hybrid configuration of the ISC and FLC (non‐model‐based controllers) for optimal positioning and anti‐swing control of the TCS. Three configurations of the ISC + FLC, namely shaper as reference input (SARI), shaper as input to the FLC (SAI2F), and shaper as input to the plant (SAI2P) were investigated to assess the optimal hybrid configuration of the ISC + FLC. The results demonstrated that the hybrid ISC + FLC scheme had improved the response of ISC by at least 150% and enhanced the oscillation reduction of FLC by 72%. Finally, these analyses showed that the ISC + FLC could achieve reasonable control of the tower crane by only considering the output of one state (position). This makes the control scheme cheaper and reduces the complexity and computational time compared to other full‐state feedback controllers.

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

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