Biju Edamana

Modeling and Optimal Low-Power On–Off Control of Thin-Film Piezoelectric Rotational Actuators

A novel open-loop minimal energy on-off servo system and control strategy are described for ensuring specified displacements from new microscale piezoelectric rotational joints under extremely strict power budgets. The rotational joints are driven by thin-film lead-zirconate-titanate actuators and are targeted for use in autonomous terrestrial microrobots. A lumped-parameter, second-order model of anticipated joint behavior is utilized to estimate the natural frequency and damping ratio of the robot joints, which, in turn, are used to identify necessary sampling rates and switching drive circuit parameters for implementation of on-off control. An identified model of leg joint behavior is then used to both verify lumped-parameter modeling and to optimize on-off input sequences to the rotary joint. The optimization procedure incorporates energy costs from both switching and holding an input voltage on microactuators that behave as a capacitive load, while ensuring that specified final states of a dynamic system are achieved at a specified point in time. Optimization is done via a new application of binary programming. In addition, modest robustness of the system response to parameter variation can be produced during control sequence generation. Optimized input sequences are applied to both macroscale piezoelectric actuators and to prototype thin-film piezoelectric leg joints, and show that specified actuator motions can be achieved with energy consumption of less than 5 μJ per movement.

Optimal Low-Power Piezoelectric Actuator Control With Charge Recovery for a Microrobotic Leg

This paper describes an efficient control strategy for a piezoelectric microactuator using charge recovery. For piezoelectric actuators, as well as other actuators that behave primarily as capacitive loads, energy consumption can be reduced by minimizing the number of times an actuator is charged and by recovering stored energy when it is turned off. An integer programming-based algorithm is used to drive microrobotic legs powered by piezoelectric actuators to a specified angle in a specified time using minimum energy. Partial charge recovery is incorporated; this allows the use of a more flexible controller than a pure on-off controller, with two or more intermediate voltage levels between the minimum and maximum voltages available to improve positioning accuracy. Simulated and experimental tests show that a prototype piezoelectric robotic leg joint achieved controlled movements with one third of the energy consumed by a pure on-off controller.

Estimation With Threshold Sensing for Gyroscope Calibration Using a Piezoelectric Microstage

A sensing estimation scheme is presented that combines analog and threshold sensing on a piezoelectric microactuator for calibration of microscale inertial sensors. Using a variation of the Kalman filter, an asynchronous threshold sensor improves state estimates obtained from less reliable analog sensor measurements of microactuator motion. The resulting velocity estimates are compared with estimates without threshold sensing, and related to feasible calibration performance for gyroscopes. Results show that incorporating threshold sensors in a projected low-noise environment based on capacitive sensing will produce high-accuracy velocity measurements at certain fixed angles, with an approximately 80% reduction in angular velocity estimation error. Experimental testing with noisier, more variable piezoelectric sensing shows improved estimation accuracy at all velocities and positions when threshold detections are added. In simulation, the addition of feedback control is shown to further improve estimation accuracy.

An optimal on-off controller with switching costs using non-linear binary programming

Autonomous systems based on MEMS devices may often be provided with very limited computational and power capacity, if control circuitry and power sources are to be miniaturized along with the electromechanical components. On-Off control can serve as an efficient methods of regulating motion of MEMS structures when power is extremely limited by allowing control to be performed using simple driving circuits and few transitions between ‘on’- and ‘off’-states. In particular, this is highly desirable for micro-robotics applications based on piezoelectric actuation. In this paper a binary programming method is used to optimize a cost function that consists of the number of switching transitions and on-time for a linear-discrete system, as the system is steered to a desired final state. This can be used to minimize power consumption in piezoelectric actuators as they move a micro-robotic leg joint to a desired position. A set of test cases is examined to explore behavior of the optimization procedure.

NARMAX identification for space weather prediction using polynomial radial basis functions

Solar storms can damage transformers, electrical networks, and satellites. In this paper, we use system identification methods to construct nonlinear time-series models that are used to predict solar wind conditions with a 27-day prediction horizon. To identify nonlinear time-series models, we use a set of basis functions to represent the nonlinear mapping. For these basis functions, we propose an alternative class of radial basis functions, which have fewer parameters that needs to be tuned by the user. Finally, we compare the predictions obtained using identified models with predictions obtained with existing models.

Control and estimation with threshold sensing for Inertial Measurement Unit calibration using a piezoelectric microstage

A threshold sensing strategy for improving measurement accuracy of a piezoelectric microactuator in calibration of miniature Inertial Measurement Units (IMUs) is presented. An asynchronous threshold sensor is hypothesized as a way to improve state estimates obtained from analog sensor measurements of microactuator motion. To produce accurate periodic signals using the proposed piezoelectric actuator and sensing arrangement, an Iterative Learning Control (ILC) is employed. Three sensing strategies: (i) an analog sensor alone with a Kalman filter; (ii) an analog sensor and threshold sensor with a Kalman filter; and (iii) an analog sensor and threshold sensor with a Kalman smoother are compared in simulation and single-axis experiments. Results show that incorporating threshold sensors in a projected low-noise environment based on capacitive sensing will produce high-accuracy velocity measurements at certain fixed angles, while experimental testing with less reliable piezoelectric sensing shows improved estimation accuracy at all velocities and positions.

Coordinated voltage conversion and low-power micro-actuator switching

Due to very low power throughput and behavior as primarily capacitive loads, voltage conversion for micro-scale piezoelectric and electrostatic actuators can be very inefficient, while analog drive circuit supply currents may also exceed actuator power consumption. When limited instead to switching commands at discrete time instants to control micro-actuator motion, it may be advantageous to coordinate operating periods of any voltage conversion circuitry with actuators. A sample scenario of a traditional boost converter driving a thin-film piezoelectric micro-robotic appendage along a trajectory is considered through simulation studies. Some ranges of target motion accuracy are achieved using less energy, up to a 25% reduction at 30 V, for a 4 V battery, when coordinating voltage converter operation, even when conversion efficiency is very low.Copyright

Low-power switching control schemes for piezoelectric micro-robotic actuators

This article describes the development of piezoelectric micro-actuators for use in micro-robotic systems, and surveys controllers and power electronics for such actuators to meet power limitations of terrestrial micro-robots with high mobility. A thin-film lead-zirconate-titanate lateral actuator design with one micron stroke and several millinewtons of actuation force is described, and sample experimental results provided. A method for integrating these actuators with flexible silicon micro-structures, and implications for micro-robotic pay-load capacity are presented. On-off control is proposed as a method to minimize energy usage by piezoelectric actuators and driving circuitry when moving a micro-robotic appendage based on these designs. Low efficiency of voltage converters and large power consumption of sensing circuitry are identified as barriers to further enhancing servo capabilities of bio-inspired terrestrial micro-robots.Copyright

A Near-Optimal Sensor Scheduling Strategy for an on–off Controller With an Expensive Sensor

This paper describes an efficient method for scheduling an energy-consuming sensor sparingly in combination with an on-off controller, specifically for a finite horizon control problem in which only end states are critical. In certain low-power applications, such as autonomous microrobotics, on-off controllers can be very efficient in operating piezoelectric actuators (and other capacitive actuation schemes) compared to traditional analog and pulsewidth modulation controllers. However, with existing sensing circuitry, sensing at the same frequency as control can be prohibitively expensive, because energy consumption in the sensing circuitry may be comparable or even much higher than energy consumption for actuation. Instead, a method is presented for best scheduling a limited number of sensor measurements and updates to control inputs during a finite horizon on-off control problem, in response to Gaussian disturbances and measurement noise. To simplify the problem, a lower bound for the expected value of a quadratic error function of the end states is found, which permits rapid evaluation of candidate sensor times. When actuator energy consumption is incorporated in the optimization, this produces a numerically efficient near-optimal strategy for determining best measurement times and updates to the control input sequence.

Optimal on-off controller with charge recovery for thin-film piezoelectric actuators for an autonomous mobile micro-robot

In this paper an efficient control strategy using charge recovery for a MEMS piezoelectric actuator is described. For piezoelectric actuators or other actuation schemes which act as capacitor loads, energy consumption can be reduced by minimizing the number of times the actuator is charged and by recovering the drained energy when it is turned off. An integer programming-based algorithm is used to drive micro-robotic legs consisting of piezoelectric actuators to a certain specific angle in a given time with the use of minimum energy. Partial charge recovery, which recovers a portion of the drained energy, is incorporated by making use of a lighter inductor. This allows the use of a more flexible controller than a pure ultra low-power on-off controller, with two or more intermediate voltage levels between the minimum and maximum voltages available to improve positioning accuracy, while also reducing energy consumption.