This article describes how an extrinsically amplified Cymbal-type piezoelectric actuator is optimized for displacement generation by using genetic algorithms in combination with COMSOL Multiphysics finite element method modeling software. The research was focused on optimizing the shape of the end cap profile in a quasi-static operation scheme in order to keep the number of parameters and calculation times at a reasonable level. In contrast to conventional linear end cap profiles, a genetic algorithm tends to generate more complex shapes and especially a corrugated structure in the vicinity of the output point of force and displacement. Modeling showed that about 26.9% higher displacement could be produced with a complex shape derived by the algorithm compared with a linear end cap profile. Moreover, about the same level of displacement as achieved with a wagon wheel transducer was obtained simply by profile optimization without material removal, which could, however, improve performance even further. The developed genetic algorithm proved to be a feasible tool for complex multi-parameter optimization, utilizable in a wide range of shape and structure optimizations for future electromechanical components.
This paper introduces a new type of piezoelectric actuator, Mikbal. The Mikbal was developed from a Cymbal by adding steel structures around the steel cap to increase displacement and reduce the amount of piezoelectric material used. Here the parameters of the steel cap of Mikbal and Cymbal actuators were optimised by using genetic algorithms in combination with Comsol Multiphysics FEM modelling software. The blocking force of the actuator was maximised for different values of displacement by optimising the height and the top diameter of the end cap profile so that their effect on displacement, blocking force and stresses could be analysed. The optimisation process was done for five Mikbal-and two Cymbal-type actuators with different diameters varying between 15-40 mm. A Mikbal with a ∅ 25 mm piezoceramic disc and a ∅ 40 mm steel end cap was produced and the performances of unclamped measured and modelled cases were found to correspond within 2.8 % accuracy. With a piezoelectric disc of ∅ 25 mm, the Mikbal created 72 % greater displacement while blocking force was decreased 57 % compared with a Cymbal with the same size disc. Even with a ∅ 20 mm piezoelectric disc, the Mikbal was able generate ~10 % higher displacement than a ∅ 25 mm Cymbal. Thus, the introduced Mikbal structure presents a way to extend the displacement capabilities of a conventional Cymbal actuator for low-to-moderate force applications.
This paper proposes a simple adaptive weight computing method for particle filters that utilizes knowledge about predictive model uncertainty. In each time step the particles are assigned into subsets based on the corresponding uncertainty estimates. The weights are then updated based on accumulated subset-inclusion and likelihood information using a discrete set of measurement likelihood functions. By controlling the aggressiveness of the weight computing, the method strives to achieve faster convergence without losing robustness to model errors. Two localization experiments are conducted to verify that the method has a clear advantage over particle filters with single likelihood function. In the first experiment we use synthetic Gaussian Process data. In the second experiment real indoor magnetic field data with very coarse interpolation and uncertainty approximation is used to verify the method's effectiveness in real-world scenarios. One of the main advantages of the proposed method is that despite its flexibility, it adds only little implementational or computational overhead to conventional particle filters.
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