Mobile Inverted Pendulum Research Articles

모바일 역진자의 효율적 수평유지 기법

A new dynamic balancing algorithm has been proposed to minimize the number of sensors necessary for the horizontal balancing of the mobile inverted pendulum while maintaining the same level of the commercial performance. The inverted pendulum technique is getting attention and there have been many researches on the Segway since the US inventor Dean Kamen commercialized. One of the major problems of the Segway is that many sensors are required for the control of the Segway, which results in the high price. In this research, a single gyro and a tilt sensor are fused to obtain the absolute tilt information, which is applied for the control of the mobile inverted pendulum. A dynamic balancing technique has been developed and applied for a robust control system against disturbances. The intelligent handling and stable curving of the Segway as a next generation mobile tool are verified with a human loading.

FPGA Control of a Mobile Inverted Pendulum Robot

The inverted pendulum is a classic problem in dynamics and control theory due to its inherently unstable nature. In the system tested, Field Programmable Gate Arrays (FPGAs) are used for the implementation of control and sensor fusion algorithms in the inertial navigation system of a Mobile Inverted Pendulum (MIP) robot. Additionally, the performance of digital PID control and Kalman filter algorithms are tested in this FPGA system. The test platform for tuning Kalman filter is designed using optical encoders as a standard reference. PWM signal generation and quadrature phase decoding of encoder pulses is accomplished using hardware description language in FPGA. The values from the inertial sensors and quadrature phase decoded values are fed into MicroBlaze, a 32-bit soft-core RISC processor, within the FPGA. The overall system demonstrates the use of low cost inertial sensors to balance a two wheeled robot. The system is presently able to balance on its own and it also serves as an extremely reconfigurable FPGA based platform to facilitate future modifications, updates and enhancements with more complex control and sensor fusion techniques.Key Terms: Mobile Inverted Pendulum System; Inverted Pendulum Robot; Inertial Navigation System; FPGA; Kalman Filter; PID Control; Soft-core ProcessorDOI: http://dx.doi.org/10.3126/jie.v8i1-2.5111Journal of the Institute of EngineeringVol. 8, No. 1&2, 2010/2011Page: 188-196Uploaded Date: 20 July, 2011