Digitally tuned analog VLSI controllers

Digital controllers have historically enjoyed many advantages over those synthesized by analog electronics, but there are still some drawbacks to discrete-time implementations of controllers and signal processing algorithms: costly conversion of analog signals to digital and back, quantization errors, digital noise, time discretization, computation of signals by one CPU, and relatively large circuitry with limited processing speed. The key disadvantage of digitals systems is the signal latency due to A/D and D/A conversion time and relatively slow signal processing. The key disadvantages of analog signal processing are: limited accuracy due to limited tolerances of transistors and limited flexibility for adaptation. When digitally tuned analog controllers are used, then both disadvantages can be eliminated. Limited tolerances of circuit elements can be also compensated by digital tuning. Furthermore, this approach gives the possibility to reconfigure the system. Digitally controlled analog circuits have the following advantages: lower cost, high speed and small signal latency, parallel processing, direct implementation of continuous time designs, and smaller system noise important for a precision control.

[1]  J. C. Gallacher,et al.  Continuous time recurrent neural networks: a paradigm for evolvable analog controller circuits , 2000, Proceedings of the IEEE 2000 National Aerospace and Electronics Conference. NAECON 2000. Engineering Tomorrow (Cat. No.00CH37093).

[2]  Dariusz Czarkowski,et al.  CMOS current-mode analog circuit building blocks for rf DC-DC converter controllers , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[3]  Philip D. Wasserman,et al.  Neural computing - theory and practice , 1989 .

[4]  D. He,et al.  Peak current-mode control for a boost converter using an 8-bit microcontroller , 2003, IEEE 34th Annual Conference on Power Electronics Specialist, 2003. PESC '03..

[5]  Bhim Singh,et al.  Development of a simple analog controller for switched reluctance motor , 2000, Proceedings of IEEE International Conference on Industrial Technology 2000 (IEEE Cat. No.00TH8482).

[6]  Y.-A. Chapuis,et al.  HDL-based methodology for VLSI design of AC motor controller , 2003 .

[7]  B.P. Muni,et al.  Evaluation of a novel analog based closed-loop sensorless controller for switched reluctance motor drive , 2001, Conference Record of the 2001 IEEE Industry Applications Conference. 36th IAS Annual Meeting (Cat. No.01CH37248).

[8]  Okyay Kaynak,et al.  Neuro-fuzzy architecture for CMOS implementation , 1999, IEEE Trans. Ind. Electron..

[9]  Bogdan M. Wilamowski Neural network architectures and learning , 2003, IEEE International Conference on Industrial Technology, 2003.

[10]  Okyay Kaynak,et al.  VLSI Implementation of Neural Networks , 2000, Int. J. Neural Syst..

[11]  Bogdan M. Wilamowski,et al.  Neural Networks and Fuzzy Systems , 2018, Microelectronics.

[12]  Sergio L. Toral Marín,et al.  Digital stochastic realization of complex analog controllers , 2002, IEEE Trans. Ind. Electron..

[13]  D. Maksimovic,et al.  Digital controller chip set for isolated DC power supplies , 2003, Eighteenth Annual IEEE Applied Power Electronics Conference and Exposition, 2003. APEC '03..