Power-Efficient Driver Circuit for Piezo Electric Actuator with Passive Charge Recovery

Abstract

Piezoelectric actuation is a promising principle for insect-scaled robots. A major concern while utilizing a piezoelectric actuator is energy loss due to its parasitic capacitance. In this paper, we propose a new concept to recover the charge stored in the parasitic capacitance; it requires only three additional lightweight passive components: two diodes and a resistor. The advantages of our concept are its small additional mass and simple operating procedure compared with existing charge recovery circuits. We provided a guideline for selecting a resistor using a simplified theoretical model and found that half of the charge can be recovered by employing a resistor that has a resistance sufficiently larger than the forward resistance of the additional diode. In addition, we experimentally demonstrated the concept. With a capacitive load (as a replacement for the piezoelectric actuator), it was successfully observed that the proposed concept decreased the power consumption to 58% of that in a circuit without charge recovery. Considering micro aerial vehicle (MAV) applications, we measured the lift-to-power efficiency of a flapping wing piezoelectric actuator by applying the proposed concept. The lift force was not affected by charge recovery; however, the power consumption was reduced. As a result, the efficiency was improved to 30.0%. We expect that the proposed circuit will contribute to the advancement of energy-saving microrobotics.

Feedforward Compensation Analysis of Piezoelectric Actuators Using Artificial Neural Networks with Conventional PID Controller and Single-Neuron PID Based on Hebb Learning Rules

“…During the experiments, it was found that the relation between the output voltage and the measured position had a factor of 4. The performance of each framework was compared using the integral of the absolute magnitude of the error (IAE) over time as a metric, which has the expression of Equation (2). The use of the error magnitude in the integral results in a sensitive expression either for positive or negative values.…”

“…Piezoelectric actuators (PEAs) are positioning systems which have been widely used in the field of micro-and nano-positioning due to their high displacement resolution (around the micrometer), large actuation force (typically several hundred of Newtons), high speed response and vast stiffness. They had also been employed in applications such as scanning probe microscopes (SPM), computer components, micro-manipulators, machine tools and energy recovery [1,2]. However, the biggest problem with PEAs are non-linearities due to the effects of hysteresis, creep, and vibrations, which can significantly degrade the system performance and even its stability.…”

Robotic micromanipulation: a) actuators and their application

“…Second, only a fraction of the input electric power is converted into mechanical work by the piezoelectric material. The rest is stored in the capacitive storage, which must be recovered to maximize the system's efficiency [34]. Third, piezoelectric materials suffer from huge nonlinearities, hysteresis and noticeable creep [30], resulting in that each given input provides an unexpected output.…”

High-Performance Tracking for Piezoelectric Actuators Using Super-Twisting Algorithm Based on Artificial Neural Networks

“…The blend is produced with the advantage of their size, which is an asset for the downsizing trend in actuators today. Due to these benefits, the applications are broad which includes energy harvesting [4], active vibration [5], motor design [6], etc. Furthermore, in recent years, the PEA has been a research aim for medical uses, such as drug delivery systems [7], micro grippers [8], spinal injection device [9], and orthodontic treatment [10].…”