Most control approaches are model-based methods and require a precise mathematical description of the considered dynamical system. System modeling offers the advantage that the controllable system dynamics can be affected by control in such a way that some given desired dynamics is achieved. However, most technical systems are complex and it is difficult and time-consuming to describe them exactly or it may even be impossible. Challenges that arise in system modeling can be for instance: parameters that are not precisely known or that vary in time, dynamics that exist but are unmodeled, or especially for modern control systems interactions with the environment that lead to unknown exogenous inputs. Consequently, it is common that a discrepancy between the modeled dynamics and the true dynamics exists. The applied controller is required to be robust in the sense that the control goals are also guaranteed to be achieved in presence of the model discrepancy. Sliding mode control (SMC) is such a robust control method. It can make the system dynamics invariant to disturbances that appear in the input channel so that the desired dynamics are still achieved. However, besides its strong robustness properties sliding mode control also has some disadvantages: Conventional sliding mode control leads to a high frequent switching effect in the input signal denoted as chattering making the controller inapplicable in practice. Higher order SMC approaches may effectively mitigate the chattering but typically require higher order time derivatives of the measured signal. As a consequence, the whole approach becomes more sensitive to noise. Adaptive SMC approaches have been developed to reduce the chattering as well. However, chattering reduction can only be achieved to a certain extend as otherwise the control goals may not be achieved anymore. The handling of constraints in the context of sliding mode control is not straight forward as due to the model uncertainty standard add-on control approaches like the invariance control ...
Contributions to Sliding Mode Control and Observation of Nonlinear Uncertain Systems
2022-08-22
Hochschulschrift
Elektronische Ressource
Englisch
Contributions to Sliding Mode Control and Observation of Nonlinear Uncertain Systems
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