This study presents a novel approach for active vibration control of a Shape Memory Alloy (SMA) von Mises structure using a bioinspired controller. A constitutive model that accurately captures the SMA thermomechanical behavior is used to describe the system dynamics. Nevertheless, this model is computationally demanding and requires the identification and adjustment of a large number of parameters, making its direct use in the controller design impractical for real-time control applications. In this context, the controller is based on the sliding mode control approach being enhanced with a neural network to compensate uncertainties and external disturbances, and it is designed using a polynomial constitutive model to approximate the system dynamics, as required by the control formulation. This model is adopted due to its simplicity and reduced number of parameters to be identified, while providing an approximate representation of the plant. Hence, the proposed control law is capable of predicting the system's dynamical behavior, adapting to changes, and learning from the system-environment interaction in an online manner. The closed-loop system's convergence is analyzed using a Lyapunov-like stability analysis, and numerical simulations demonstrate the effectiveness of the proposed strategy for suppressing undesired vibrations in the presence of nonlinear effects and model mismatch. Overall, the proposed approach combines reduced computational complexity with online adaptation capabilities, providing an efficient framework for active vibration control of SMA structures.

This paper investigates a novel adaptive energy harvester that synergistically combines piezoelectric material and shape memory alloy (SMA). The piezoelectric material converts mechanical into electrical energy while an SMA element is used as a stopper that introduces nonsmooth nonlinearity. Nonsmooth systems operate in different modes, with and without contact, presenting rich dynamics that can be useful to enhance energy harvesting capacity. Besides, the SMA can be exploited by considering two different behaviors: morphing ability to change the gap distance from temperature variations; energy dissipation due to hysteretic behavior during contact dynamical mode, contributing to the structural safety of the device. A mathematical model is proposed considering a linear constitutive model to describe the piezoelectric electromechanical behavior while a model with polynomial phase transformation kinetics is employed to describe SMA thermomechanical behavior. Numerical simulations are carried out evaluating the influence of nonlinear characteristics due to the contact and due to SMA phase transformations. The investigation establishes a comparison of the novel device with the linear device and with the nonlinear device with elastic stopper. Results show that the adaptive harvester has better performance for different operational conditions characterized by base amplitude and frequency. Therefore, the synergistic use of smart materials is a promising strategy to enhance energy harvesting capacity, especially considering ambient uncertainties.

The conversion of ambient mechanical vibrational energy into electrical energy through piezoelectric devices has received an increasing attention in recent years. The main challenges are to develop efficient devices that operate over a wide frequency range, adapting to diverse environmental energy sources. This work presents a framework for the analysis of a nonlinear vibration-based energy harvesting devices combining the nonlinear finite element method with a reduced-order model, which provides a broader dynamical investigation. On this basis, a flexible tool is developed, allowing the multimodal analysis of nonlinear systems. A bistable piezoelectric energy harvesting device is investigated considering the influence of multimodal and nonlinear effects on the system performance. Bistability is due to magnetic interactions among magnets and the beam tip, modeled by cubic nonlinearities. Numerical simulations show the influence of vibration sources on the dynamics and performance of the device. Nonlinear effects furnish rich dynamics, presenting periodic and chaotic responses. All these effects can be combined to enhance energy harvesting capacity.

Hysteretic response of smart materials has complex mathematical modeling. Thermodynamic-based constitutive models belong to an important class of models and data-driven models are interesting alternatives that avoid complex algorithms and parameter determinations. The classical Preisach model describes multidisciplinary hysteretic behavior employing mathematical operators in a triangular domain. The Everett function is an alternative build a surface from experimental data, replacing the original integral form to a summation. This paper proposes a novel approach, extending the Preisach triangular domain to a prismatic domain that allows a broader description of distinct phenomena. The idea is to use the Preisach approach for different triangles and then performing a interpolation for a prismatic domain, enabling the representation of distinct phenomena that, otherwise would not be described. Shape memory alloys (SMAs) are employed as a representative example of smart materials. Experimental tests are developed in order to define reference cases to be analyzed. Numerical simulations are carried out and compared with experimental data, evaluating the model capabilities under different loading conditions. Specifically, temperature-dependent and cyclic-dependent behaviors are of concern. The results show the model ability to describe the general thermomechanical behavior of shape memory alloy hysteretic behavior, being in close agreement with experimental data.

Origami has been inspirating the development of novel engineering systems and structures. The traditional waterbomb folding pattern is one of the most widely employed pattern and its description from the unit-cell is related to multiple degrees of freedom (DoF) systems. This work investigates the nonlinear dynamics and chaos of a waterbomb origami through its unit-cell, considering different symmetry hypotheses that simplify its kinematics, resulting in 1-DoF and 2-DoF dynamical systems. The investigation starts with a kinematic analysis of the waterbomb folding pattern and afterward, a reduced-order dynamical model with lumped masses on vertices and torsional springs on creases is built. Symmetry assumptions are discussed, identifying the differences induced by either geometrical nonlinearities or external stimuli. Numerical simulations are carried out showing details of the system nonlinear dynamics, showing intricate situations such as chaos. The comparison among different symmetry conditions provides a qualitative picture of the system dynamics, showing significative differences and highlighting the importance of the origami mechanical behavior comprehension, its modeling and nonlinear dynamics for a proper design of origami-inspired systems.

The use of smart materials as transducers in mechanical energy harvesting systems has gained significant attention in recent years. Despite the numerous proposed solutions in the literature, challenges still exist in terms of their implementation within limited spaces while maintaining optimal performance. This paper addresses these challenges through the concepts of compactness and space-efficient design, as well as the incorporation of nonlinear characteristics and additional degrees-of-freedom. A multistable dual beam nonlinear structure featuring two magnetic interactions and two piezoelectric transducers is presented. A reduced order model with 2-degrees-of-freedom is established based on the harvester structure in order to capture the essential qualitative characteristics of the system. Stability analysis demonstrates that the combination of two nonlinear magnetic interactions furnish unprecedented multistable characteristics to this type of harvester. A framework using a nonlinear dynamics perspective is established to analyze multistable systems based on energy harvesting purposes. Different dynamical and stability characteristics are determined by the differences in the system stiffness ratio. Parametric analyses are carried out classifying regions of high performance in the external excitation parameter space. These regions are associated with rich and complex dynamics. Finally, a comprehensive comparison is conducted between the proposed harvester and the classical bistable harvester, revealing improvements in performance across nearly all relevant conditions. These findings highlight the enhanced capabilities of the proposed harvester design, solidifying its potential of application in diverse energy harvesting scenarios.

Cardiac rhythms are related to heart electrical activity, being the essential aspect of the cardiovascular physiology. Usually, these rhythms are represented by electrocardiograms (ECGs) that are useful to detect cardiac pathologies. Essentially, the heart activity starts in the sinoatrial node (SA) node, the natural pacemaker, propagating to the atrioventricular node (AV), and finally reaching the His-Purkinje complex (HP). This paper investigates the control of cardiac rhythms in order to induce normal rhythms from pathological responses. A mathematical model that presents close agreement with experimental measurements is employed to represent the heart functioning. The adopted model comprises a network of three nonlinear oscillators that represent each one of the cardiac nodes, connected by delayed couplings. The pathological behavior is induced by an external stimulus in the SA node. An adaptive controller is proposed acting in the SA node considering an strategy based on the signal obtained by the natural pacemaker and its regularization. The incorporation of adaptive compensation in a Lyapunov-based control scheme allows the compensation for the unknown dynamics. The controller ability to deal with interpatient variability is evaluated by assuming that the heart model is not available to the controller design, being used only in the simulator to assess the control performance. Results show that the adaptive term can reduce the control effort by around 3% while reducing the tracking error by 20%, when compared to the conventional feedback approach. Additionally, the controller can avoid abnormal rhythms, turning the ECG closer to the expected normal behavior and preventing critical cardiac responses. Therefore, this work demonstrates that an adaptive controller can be used to regulate the ECG signal without prior information about the system and disregarding inter- and intrapatient variability.