Adaptive Output Feedback Control for 5-DOF Varying-Cable-Length Tower Cranes With Cargo Mass Estimation

Abstract

Tower crane systems exhibit high nonlinearity and underactuation, making the control issue challenging. Most reported methods for tower crane systems utilize linearized models, and accurate plant parameters (e.g., cargo mass, jib moment inertia) and full state feedback are usually required; moreover, most existing works only consider a part of the crane motions, and the control issue of five degree-of-freedom (5-DOF) tower cranes (i.e., 2-DOF cargo swing, slew, hoisting, and translation) is still open. However, tower cranes are practically influenced by uncertainties and disturbances, which may make linearized models ineffective; additionally, exact values of plant parameters may be difficult to obtain, and velocity signals are usually not directly measurable in practice. To address the aforementioned problems, this article proposes an adaptive output feedback control method for 5-DOF varying-cable-length tower cranes. As far as we know, this article provides the first adaptive output feedback controller, designed and analyzed without linearizing the dynamic equations, which can simultaneously achieve cargo hoisting/lowering, jib slew, trolley translation, and swing suppression, by avoiding using velocity-related feedback signals. Resorting to an elaborately constructed virtual spring-mass system, the control objectives are satisfactorily achieved even without involving any velocity signals with theoretical/experimental guarantee. Moreover, by elaborately designing a new adaptive law, the exact values of unknown cargo masses can be estimated through online identification. We provide rigorous stability/convergence analysis for the closed-loop system. Hardware experiment results are included for effectiveness/robustness verification.