Sliding Mode Control

Abstract

Sliding mode theory is currently one of the most significant research topics within the control engineering domain. Moreover, recently a number of important applications of the theory in the field of power electronics, motion control, robotics, bioprocess, etc. have also been reported. Therefore, this Special Issue presents both novel trends in fundamental research on sliding mode control (SMC) and some successful engineering applications. The special issue consists of 10 papers. The first paper by T. Floquet et al. considers the problem of designing an observer for a multivariable linear system partially driven by unknown inputs. Such a problem arises in systems subject to disturbances or with inaccessible/unmeasurable inputs and has many applications such as fault detection and isolation (FDI), parameter identification and cryptography. Floquet et al. attempt to broaden the class of systems for which these observers can be designed. Specifically, the paper shows how the relative-degree-one condition can be weakened if a classical sliding mode observer is combined with sliding mode exact differentiators to generate additional independent output signals from the available measurements. In the second paper by X. G. Yan and C. Edwards, a sensor FDI scheme for non-linear systems is considered. A non-linear diffeomorphism is introduced to explore the system structure and a simple filter is used to ‘transform’ the sensor fault problem into a pseudo-actuator fault scenario. A sliding mode observer is designed to reconstruct the sensor fault precisely if the system does not experience any uncertainty and to estimate the sensor fault when uncertainty exists. The reconstruction and estimation signals are based only on the available information and thus can be implemented online. The next paper written by A. Topalov et al. is devoted to neural network-based sliding mode controllers. In this work, an innovative dynamical online learning algorithm for robust model-free neuro-adaptive control of a class of non-linear systems with uncertain dynamics is proposed. The algorithm is experimentally tested in order to evaluate its performance and practical feasibility for industrial application. The control application studied is the trajectory tracking control task for the first three joints of an open architecture-articulated robot manipulator. The control scheme makes use of variable structure systems theory and the feedback–error–learning concept. In the fourth paper, the control of dynamic non-linear systems by output feedback is addressed by T. R. Oliveira et al. A model-reference tracking SMC approach is adopted to develop a controller for uncertain plants with arbitrary relative degree and unknown control direction. The uncertainty of the control direction is circumvented by a switching mechanism that adjusts the control sign through a monitoring function that depends on an appropriate auxiliary error. The relative degree compensation and the ultimate finite time or exponential convergence of the tracking error to zero are achieved by means of a hybrid lead filter based on the switching between a conventional linear differentiator and a robust exact differentiator. The next paper by A. Ferrara and C. Lombardi deals with the problem of the interaction control of robot manipulators, the end-effector of which is expected to enter in contact with the environment, characterized by a known elastic constant. The model of the manipulator is affected by uncertainties in the terms representing the torques induced by the Coriolis and centrifugal forces, and the friction torques, so that a classical impedance control scheme cannot be adopted. Therefore, in this paper the use of second-order SMC is investigated and the novel idea is developed to circumvent the chattering problem while extending the applicability of the impedance control philosophy to the uncertain case. Another contribution to the control of systems in interaction with their environme