In this article, the modeling and control problem of a Pneumatic Artificial Muscle (PAM) is being considered. The PAM is an actuator characterized by a decrease in the actuating length when pressurized. Its non-linear nature and time-varying parameters cause difficulties in modeling their characteristics, as well as in designing controllers for high-performance positioning systems. A constrained linear and PieceWise Affine (PWA) system model approximation is formulated and a control scheme composed of: a) a feedforward term regulating control input at specific setpoints, and b) a Constrained Finite Time Optimal Controller (CFTOC) handling any deviations from the system's equilibrium points is being synthesized. Extended experimental studies are utilized to prove the efficacy of the suggested controller.

This work offers a reliable solution to the detection of broken rotor bars in induction machines with a novel methodology, which is based on the fact that the fault related harmonics will have oscillating amplitudes due to the speed ripple effect. The method consists of two main steps: Initially, a timefrequency transformation is used and the focus is given on the steady-state regime; thereupon, the fault related frequencies are handled as periodical signals over time and the classical Fast Fourier Transform is used for the evaluation of their own spectral content. This leads to the discrimination of sub-components related to the fault and evaluation of their amplitudes. The versatility of the proposed method relies on the fact that it reveals the aforementioned signatures to detect the fault, regardless of the spatial location of the broken rotor bars. Extensive finite element simulations on a 1.1MW induction motor and experimental testing on a 1.1kW induction motor lead to the conclusion that, the method can be generalized on any type of induction motor independently from the size, power, number of poles and rotor slot numbers.

the broken rotor bar diagnosis using time-frequency analysis: "Is one spectral representation enough for the characterization of monitored signals?"', Iet electric power applications.

This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.