Publications

In this work, an online optimal trajectory design strategy based on Soft Switching Multiple Model Predictive Control (SSM-MPC) for an industrial pick-and-place machine is proposed. By using the SSM-MPC, the generated trajectory will be adaptive to system parameters variations such as load inertia, etc.

Dynamic models of mechatronic systems are abundantly used in the context of motion control and design of complex servo applications. In practice, these systems are often plagued by unknown interactions, which make the physics-based relations of the system dynamics only partially known. This article presents a neural network augmented physics (NNAP) model as a combination of physics-inspired and neural layers. The neural layers are inserted in ...

The high functional performance exhibited by modern applications is very often established by an aggregation of various intricate mechanical mechanisms, providing the required motion dynamics to the overall system. Above all, the mechanism's behavior should be reliable for a wide range of operating conditions to assure at all times appropriate functioning of the entire application. In particular, cam-follower mechanisms, which translate a ...

In this article, we propose a simple, practical, and intuitive approach to improve the performance of a conventional controller in uncertain environments using deep reinforcement learning while maintaining safe operation. Our approach is motivated by the observation that conventional controllers in industrial motion control value robustness over adaptivity to deal with different operating conditions and are suboptimal as a consequence. ...

This letter aims to investigate the robust stability of an interval fractional-order plant with an interval time delay by a general form of fractional-order controllers. Based on a simple graphical procedure, necessary and sufficient criteria are proposed to analyze the robust stability of an interval fractional-order plant. Then, the idea of "robust stability testing function" is extended to analyze the robust stability of the considered type ...

In this paper, we investigate two ideas in the context of the interpolation-based optimization paradigm tailored to derivative-free black-box optimization problems. The proposed architecture maintains a radial basis function interpolation model of the actual objective that is managed according to a trust-region globalization scheme. We focus on two distinctive ideas. Firstly, we explore an original sampling strategy to adapt the interpolation ...

This study investigates the robust stability analysis of an unstable second order plus time-delay (SOPTD) plant by using Fractional-Order Proportional Integral (FOPI) controllers. We assume that there are simultaneous uncertainties in gain, time-constants, and time-delay of the plant. At first, a graphical method is provided for a robust stability analysis of the closed-loop system. Then, a robust stability checking function is introduced to ...

This article presents an application of neural network-based Model Predictive Control (MPC) to improve the wind turbine control system's performance in providing frequency control ancillary services to the grid. A closed-loop Hammerstein structure is used to approximate the behavior of a 5MW floating offshore wind turbine with a Permanent Magnet Synchronous Generator (PMSG). The multilayer perceptron neural networks estimate the aerodynamic ...

The intermittent nature of wind speed imposes a nonlinear behavior on the dynamics of the wind turbine. Consequently, relying on one linear controller tuned to a single specific operating point cannot guarantee a feasible performance in the whole operating region despite providing a fast solution. Besides, wind speed variations cause oscillations in the output power of the wind turbine. To tackle these issues, the Soft Switching Multiple Model ...