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Reliable systems for micro aerial vehicles -- SoC control solution

X. Zhang, Washington University

October 30, 2017

X. Zhang, Washington UniversityOctober 30, 2017

Editor's Note: Embedded designers must contend with a host of challenges in creating systems for harsh environments. Harsh environments present unique characteristics not only in terms of temperature extremes but also in areas including availability, security, very limited power budget, and more. In Rugged Embedded Systems, the authors present a series of papers by experts in each of the areas that can present unusually demanding requirements. A separate excerpt of the book addresses fundamental concerns in reliability and system resiliency.

Elsevier is offering this and other engineering books at a 30% discount. To use this discount, click here and use code ENGIN317 during checkout.

Adapted from Rugged Embedded Systems, Computing in Harsh Environments, by Augusto Vega. Pradip Bose, Alper Buyuktosunoglu.

 

CHAPTER 7. Reliable electrical systems for micro aerial vehicles and insect-scale robots: Challenges and progress (Cont.)
By X. Zhang, Washington University, St. Louis, MO, United States

4 BrainSoC

As described in the previous section, building the RoboBee system is truly a multidisciplinary undertaking, in this section we will zoom into its electronic subsystem and in particular dive into the custom designed system-on-chip (SoC) acting as the “brain” for RoboBee, which we nicknamed BrainSoC.

4.1 RoboBee’s ELECTRONIC SUBSYSTEM

The ultimate goal of autonomous flight requires converting the external bench-top test equipment into customized electronic components that the robot can carry within its tight payload budget. Towards this end, we designed an energy-efficient BrainSoC to process sensor data and send wing flapping control signals to a power electronics unit (PEU) that generate 200–300V sinusoids for driving a pair of piezoelectric actuators to flap each individual wing [10]. Fig. 1 is a cartoon illustration of the connections between the BrainSoC and the power electronics.

To understand the basic operation of the power electronics, we first have to revisit the mechanism of exciting the flapping wings with piezoelectric actuators (Fig. 2). Electrically, these layered actuators can be modeled as capacitors. To generate sufficient wing flapping amplitude, these actuators need to be driven by a sinusoidal waveform of 200–300 V at the mechanical resonant frequency of the robot, approximately at 100 Hz. In one of our schemes, we fix the bias across the top and bottom layers of the actuator and use the PEU to drive the middle node of the actuator with a sinusoidal signal.

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FIG. 1 Illustration of different functional components connected through the substrate flexible PCB, including the BrainSoC chip and the high voltage IC chip for the power electronics unit (PEU), in the RoboBee electrical system. (inset) The relative foot print of the components compared to a U.S. five-cent coin.

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FIG. 2 (A) The voltage-driven piezoelectric bimorph that generates bidirectional wing-flapping forces in RoboBee; (B) the layered structure in the piezoelectric bimorph; and (C) the equivalent electrical circuit model for the piezoelectric actuator.

To provide the required drive signal in an efficient manner, a two-stage design is adopted for the PEU. The first stage is a tapped-inductor boost converter built with discrete components, and it outputs the high voltage bias VDDH in the 200–300 V range for the second stage. The second stage is implemented as a high voltage integrated circuit chip using double diffused metal oxide semiconductor (DMOS) transistors in a 0.8 μm 300 V BCD (Bipolar-CMOS-DMOS) process. It consists of two linear driver channels, connecting to the middle node of the left and right actuators, respectively. To generate the desired sinusoidal waveform for the drive signal, the controller of the linear drivers uses pulse frequency modulation (PFM) to encode the slope of the sinusoidal drive signals. Recall from the previous section that changing the shapes of these drive signals with respect to each other could result in roll, pitch, and, yaw rotation of the robot—shifting the drive signals up causes the robot to pitch forward, while applying different amplitudes to the left and right actuator results in roll; skewing the upward and downward slew of the drive signals result in yaw rotation (Fig. 3). As indicated by the block diagram in Fig. 4, the desired drive signal is generated by a feedback loop that relies on an embedded controller to calculate the exact sequence of the PFM pulses based on the current signal level and the high-level rotation command. More technical details on the design consideration and performance of the power electronic unit can be found in our recent paper [11].

We approach the RoboBee electronic system design with a multichip strategy, because the power electronics require specialized DMOS process that can tolerate extremely high breakdown voltages, while the real-time computational demand for autonomous flight control calls for faster digital logic circuits using more advanced CMOS process at smaller technology node. At the same time, since the multichip system has to fit within stringent weight, size, and power budget, we would like to minimize the use of external discrete components and to directly power off battery.

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FIG. 3 Drive signals for the piezoelectric actuator to generate three degree-of-freedom maneuver— roll, pitch, and yaw.

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FIG. 4 Block diagram of the two-stage PEU used for the RoboBee. (inset) The drive signal generated by the PEU for the piezoelectric actuator and the corresponding pulse modulation signals.

All these design constraints lead to the decision of a custom-designed SoC that embeds a multitude of functionalities into a single chip including integrated voltage regulator (IVR), analog to digital converters (ADC), multiple clock generators, and a computational core with heterogeneous architecture.

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