Disturbance-Compensation-Based Continuous Sliding Mode Control for Overhead Cranes With Disturbances

Abstract

For practical mechanical systems, uncertainties/disturbances, such as unmodeled dynamics and frictions, are nonignorable factors. For existing control methods, these factors are usually neglected or addressed by a robust way. As a consequence, the nominal control performance of these methods is sacrificed. Moreover, there exists the chattering problem for some existing robust methods, such as sliding mode control laws. To deal with these drawbacks, a continuous global sliding mode controller along with a nonlinear disturbance observer is designed for the regulation and disturbance estimation control of the overhead crane system. Specifically, the original crane dynamic model is transformed into a quasi-integrator-chain form through some transformations. Then, a nonlinear disturbance observer is designed and a continuous global sliding mode control method is introduced on the basis of the constructed disturbance observer. The stability and convergence characteristics are proven through rigorous theoretical analysis. Finally, to demonstrate the performance of the designed controller, a series of experimental tests are performed, and a comparison study between the devised method here and an existing method is given. Note to Practitioners —This article is motivated by the desire to deal with the regulation and disturbance rejection of the overhead crane system. In practical applications, uncertainties/disturbances are unavoidable problems for overhead cranes. For most existing methods, these issues are usually addressed in a robust way. To handle these existing problems, a nonlinear disturbance observer and a continuous global sliding mode controller are proposed for the regulation and disturbance estimation control of the overhead crane system. The disturbance observer is introduced to estimate and compensate for uncertain disturbances, and the sliding mode controller is designed to guarantee the convergence of the state variables of the closed-loop system. In the future, we will try to apply this method to practical overhead cranes.