This paper mainly focuses on various types of robots driven or actuated by shape memory alloy (SMA) element in the last decade which has created the potential functionality of SMA in robotics technology, that is classified and discussed. The wide spectrum of increasing use of SMA in the development of robotic systems is due to the increase in the knowledge of handling its functional characteristics such as large actuating force, shape memory effect, and super-elasticity features. These inherent characteristics of SMA can make robotic systems small, flexible, and soft with multi-functions to exhibit different types of moving mechanisms. This article comprehensively investigates three subsections on soft and flexible robots, driving or activating mechanisms, and artificial muscles. Each section provides an insight into literature arranged in chronological order and each piece of literature will be presented with details on its configuration, control, and application.
A dual input DC-DC converter with dual boost and integrated voltage multiplier cell operating at duty cycles larger than 0.5 is a necessity to achieve a high voltage gain for energy systems possessing two independent renewable energy resources. Output voltage regulation during load changes and input disturbances is the requisite of an energy system, which is achieved by the implementation of a suitable control action, which further requires the dynamic model of the converter. The modelling of this higher order converter with overlapping switching signals is complicated. The small-signal transfer function model based on state-space averaging followed by small-signal linearisation is verified using MATLAB and powersim (PSIM). The output voltage to duty cycle transfer functions significantly contributes to representing the converter dynamics from which its right-half s-plane zero is analysed. Since it is a non-minimum phase system, a dual loop control strategy is adopted. Voltage regulation and active current sharing are ensured from the simulation and experimental responses of the uncompensated and compensated systems. Further, from the derived integer-order converter model a fractional controller is designed and its dynamic response is compared with the traditional controller. A 200 W prototype of the converter is developed, and the control is implemented using field-programmable gate array.
Self-sensing actuation of shape memory alloy (SMA) means to sense both mechanical and thermal properties/variables through the measurement of any internally changing electrical property such as resistance/inductance/capacitance/phase/frequency of an actuating material under actuation. The main contribution of this paper is to obtain the stiffness from the measurement of electrical resistance of a shape memory coil during variable stiffness actuation thereby, simulating its self-sensing characteristics by developing a Support Vector Machine (SVM) regression and nonlinear regression model. Experimental evaluation of the stiffness of a passive biased shape memory coil (SMC) in antagonistic connection, for different electrical (like activation current, excitation frequency, and duty cycle) and mechanical input conditions (for example, the operating condition pre-stress) is done in terms of change in electrical resistance through the measurement of the instantaneous value. The stiffness is then calculated from force and displacement, while by this scheme it is sensed from the electrical resistance. To fulfill the deficiency of a dedicated physical stiffness sensor, self-sensing stiffness by a Soft Sensor (equivalently SVM) is a boon for variable stiffness actuation. A simple and well-proven voltage division method is used for indirect stiffness sensing; wherein, voltages across the shape memory coil and series resistance provide the electrical resistance. The predicted stiffness of SVM matches well with the experimental stiffness and this is validated by evaluating the performances such as root mean squared error (RMSE), the goodness of fit and correlation coefficient. This self-sensing variable stiffness actuation (SSVSA) provides several advantages in applications of SMA: sensor-less systems, miniaturized systems, simplified control systems and possible stiffness feedback control.
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