Real-Time Parameter Estimation of PMDC Motors Using Quantized Sensors

Establishing real-time models for electric motors is important when capturing authentic dynamic behavior of the motors to improve control performance, enhance robustness, and support diagnosis. Quantized sensors are less expensive, and remotely controlled motors mandate signal quantization. Such limitations on observations introduce challenging issues in motor parameter estimation. This paper develops estimators for model parameters of permanent-magnet direct current (PMDC) motors using quantized speed measurements. A typical linearized model structure of PMDC motors is used as a benchmark platform to demonstrate the technology and its key properties and benefits. Convergence properties are established. Simulations and experimental studies are performed to illustrate potential applications of the technology.