Ramesh Pawase* and N.P. Futane Pages 1 - 15 ( 15 )
Background & Objective: MEMS-based gyroscopes are used in angular rate detection where precision is an important parameter however, gyroscope output is limited by angular rate error. For minimizing these types of non-idealities, conventional external hardware-based analog or digital circuits have limitations for use in compact applications. CMOS analog ASIC for angular rate error compensation is necessary as both MEMS-CMOS technologies are supplementary and compatible. In this paper, the output of MEMS gyroscope is taken as input for the compensation circuit which results in compensated angular rate. ANN is used in intelligent compensation circuit for error reduction in which offline data is trained and minimum optimum error of MSE of 1.72e-4 is achieved. ANN uses tan sigmoidal activation function and back propagation trained MLP model with three neurons in the hidden layer. The equivalent ANN is implemented by CMOS ASIC where each neuron is implemented using Gilbert multiplier cell, differential analog adder, and differential amplifier as tan sigmoidal circuit using OrCAD-PSpice 10.5 with 0.35 μm technology. These blocks consist of differential configuration which has the capability of common mode interference rejection as noise becomes comparable at lower values of input analog signal. The entire ASIC consumes 77.8mW of power which is far less and compact in size as compared to available external hardware interface circuits. MEMS gyroscope with proposed analog ASIC becomes smart sensor with ANN based intelligent interface circuit.
Conclusion: The proposed compensation cum interface circuit gives the average angular rate error of 1.91% in the range of minimum 0 % to maximum 27 % leading to improved accuracy.
MEMS Gyroscope, Angular Rate Error, Compensation, Analog ASIC
Dept. of E&TC, SITRC Nasik, Savitribai Phule Pune University, 422608, Dept. of E&TC, Government College of Engineering, Awsari, Savitribai Phule Pune University, 412405