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In this contribution, an intelligent controller is proposed for an underactuated overhead container crane subject to both parameter uncertainties and unmodeled dynamics. The adopted approach is based on the sliding mode method to confer robustness against modeling inaccuracies and external disturbances. Additionally, an adaptive fuzzy inference system is embedded within the control law to improve set-point regulation and trajectory tracking. In order to evaluate the performance of the proposed intelligent scheme, the control law was implemented and tested in a 1:6 scale experimental container crane, available at the Institute of Mechanics and Ocean Engineering at Hamburg University of Technology. The obtained experimental results demonstrate not only the feasibility of the proposed scheme, but also its improved efficacy for both stabilization and trajectory tracking problems.

The dead-zone nonlinearity is frequently encountered in many industrial automation equipment and its presence can severely compromise control system performance. Due to the possibility to express human experience in an algorithmic manner, fuzzy logic has been largely employed in the last decades to both control and identification of uncertain dynamical systems. In spite of the simplicity of this heuristic approach, in some situations a more rigorous mathematical treatment of the problem is required. In this work, an adaptive fuzzy controller is proposed for nonlinear systems subject to dead-zone input. The convergence properties of the tracking error will be proven using Lyapunov stability theory and Barbalat's lemma. An application of this adaptive fuzzy scheme to a Van der Pol oscillator is introduced to illustrate the controller design method. Numerical results are also presented in order to demonstrate the control system performance., Comment: arXiv admin note: substantial text overlap with arXiv:2205.13669; text overlap with arXiv:2205.15639, arXiv:2205.13344, arXiv:2205.13343

Electrohydraulic servosystems are widely employed in industrial applications such as robotic manipulators, active suspensions, precision machine tools and aerospace systems. They provide many advantages over electric motors, including high force to weight ratio, fast response time and compact size. However, precise control of electrohydraulic actuated systems, due to their inherent nonlinear characteristics, cannot be easily obtained with conventional linear controllers. Most flow control valves can also exhibit some hard nonlinearities such as dead-zone due to valve spool overlap. This work describes the development of an adaptive fuzzy controller for electrohydraulic actuated systems with unknown dead-zone. The stability properties of the closed-loop systems was proven using Lyapunov stability theory and Barbalat's lemma. Numerical results are presented in order to demonstrate the control system performance., Comment: arXiv admin note: substantial text overlap with arXiv:2205.13343, arXiv:2205.13669

This paper presents an intelligent controller for uncertain underactuated nonlinear systems. The adopted approach is based on sliding mode control and enhanced by an artificial neural network to cope with modeling inaccuracies and external disturbances that can arise. The sliding surfaces are defined as a linear combination of both actuated and unactuated variables. A radial basis function is added to compensate the performance drop when, in order to avoid the chattering phenomenon, the sign function is substituted by a saturation function in the conventional sliding mode controller. An application of the proposed scheme is introduced for an inverted pendulum, in order to illustrate the controller design method, and numerical results are presented to demonstrate the improved performance of the resulting intelligent controller., Comment: References added. This is a slightly expanded version of the work originally presented at DINAME 2017 - 17th International Symposium on Dynamic Problems of Mechanics, 2017, S\~ao Sebasti\~ao, Brazil

Specific solutions of the nonlinear Schr\"odinger equation, such as the Peregrine breather, are considered to be prototypes of extreme or freak waves in the oceans. An important question is, whether these solutions also exist in the presence of gusty wind. Using the method of multiple scales, a nonlinear Schr\"odinger equation is obtained for the case of wind forced weakly nonlinear deep water waves. Thereby, the wind forcing is modeled as a stochastic process. This leads to a stochastic nonlinear Schr\"odinger equation, which is calculated for different wind regimes. For the case of wind forcing which is either random in time or random in space, it is shown that breather type solutions such as the Peregrine breather occur even in strong gusty wind conditions., Comment: 30 pages, 15 figures