This paper is dedicated to the analyses of the effect of uncertain parameters on the dynamic behavior of a flexible rotor containing two rigid discs and supported by two fluid film bearings. A stochastic method has been extensively used to model uncertain parameters, i.e., the so-called Monte Carlo simulation. However, in the present contribution, the inherent uncertainties of the bearings' parameters (i.e. the oil viscosity as a function of the oil temperature, and the radial clearance) are modeled by using a fuzzy dynamic analysis. This alternative methodology seems to be more appropriated when the stochastic process that models the uncertainties is unknown. The analysis procedure is confined to the time domain, being generated by the envelopes of the rotor orbits and the unbalance responses obtained from a run-down operating condition. The hydrodynamic supporting forces are determined by considering a nonlinear model, which is based on the solution of the dimensionless Reynolds' equation for cylindrical and short journal bearings. This numerical study illustrates the versatility and convenience of the mentioned fuzzy approach for uncertainty analysis. The results from the stochastic analysis are also presented for comparison purposes.

Parallel mechanisms are unavoidably subjected to uncertainties. These uncertainties produce a small variation of link lengths and joints position associated with the clearances. Therefore, this contribution aims at analyzing the effect of these uncertainties on the kinematic performance of the mechanism by examining the kinematic performance atlases. Initially, the complete kinematic model of the mechanism is formulated by considering the uncertainties thar are included in the modeled. The kinematic performance with the uncertainties is computed by using the Monte Carlo method. Then, the kinematic performance atlases based on workspace size and kinematic dexterity are analyzed including the uncertainties. Finally, the kinematic accuracy is evaluated for different link lengths in order to show the correspondent relationship with the kinematic performance atlases.

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The paper addresses the optimal design of parallel manipulators based on multi-objective optimization. The objective functions used are: Global Conditioning Index (GCI), Global Payload Index (GPI), and Global Gradient Index (GGI). These indices are evaluated over a required workspace which is contained in the complete workspace of the parallel manipulator. The objective functions are optimized simultaneously to improve dexterity over a required workspace, since single optimization of an objective function may not ensure an acceptable design. A Multi-Objective Evolution Algorithm (MOEA) based on the Control Elitist Non-dominated Sorting Genetic Algorithm (CENSGA) is used to find the Pareto front.

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This paper is dedicated to the analysis of uncertainties affecting the load capability of a 4-pad tilting-pad journal bearing in which the load is applied on a given pad load on pad configuration (LOP). A well-known stochastic method has been used extensively to model uncertain parameters by using the so-called Monte Carlo simulation. However, in the present contribution, the inherent uncertainties of the bearing parameters (i.e., the pad radius, the oil viscosity, and the radial clearance; bearing assembly clearance) are modeled by using a fuzzy dynamic analysis. This alternative methodology seems to be more appropriate when the stochastic process that characterizes the uncertainties is unknown. The analysis procedure is confined to the load capability of the bearing, being generated by the envelopes of the pressure fields developed on each pad. The hydrodynamic supporting forces are determined by considering a nonlinear model, which is obtained from the solution of the Reynolds equation. The most significant results are associated to the changes in the steady-state condition of the bearing due to the reaction forces that are modified according to the uncertainties introduced in the system. Finally, it is worth mentioning that the uncertainty analysis in this case provides relevant information both for design and maintenance of tilting-pad hydrodynamic bearings.

Purpose This paper aims to present the optimal design procedure of a symmetrical 2-DOF parallel planar robot with flexible joints by considering several performance criteria based on the workspace size, dynamic dexterity and energy of the control. Design/methodology/approach Consequently, the optimal design consists in determining the dimensional parameters to maximize the size of the workspace, maximize the dynamic dexterity and minimize the energy of the control action. The design criteria are derived from the kinematics, dynamics, elastodynamics and the position control law of the robot. The analysis of the design criteria is performed by means of the design space and atlases. Findings Finally, the multi-objective design optimization derived from the optimal design procedure is solved by using multi-objective genetic algorithms, and the results are analyzed to assess the validity of the proposed approach. Originality/value An alternative approach to the design of a planar parallel robot with flexible joints that permits determining the structural parameters by considering kinematic, dynamic and control operational performance.

The technology associated with active magnetic bearings has been widely used in the last years and can be considered as being one of the most promising solutions for several applications in rotating machinery. Lubricants are not necessary, and high rotation speeds are reached without any relevant heating. Active magnetic bearings are classified as mechatronic systems because they are composed of mechanical and electronic parts that are controlled by using dedicated software. In this context, the present work is devoted to the design of robust controllers applied to supercritical rotors supported by active magnetic bearings. For this aim, numerical and experimental tests were carried out. Different from previous studies reported in the literature, the present contribution proposes a novel design procedure to robustify the neuro-fuzzy controller of a rotor supported by active magnetic bearings based on optimal robust design. This optimal design procedure tunes the robust neuro-fuzzy controller taking into account the optimal balance between vibration attenuation performance and robustness, that is the increase in vibration attenuation implies the reduction in the robustness. The first stage of the controller synthesis is dedicated to the specification of all design requirements. Then, the adaptative neuro-fuzzy controller was obtained, starting from the determination of the plant dominant poles and finally performing the model-based analysis of the system stability and performance. Finally, the vibration control performance and robustness are optimally balanced by using a robust optimization procedure. The behavior of the controller was evaluated by investigating the unbalance response of the rotating system. The obtained results demonstrated the effectiveness of the conveyed approach.