Bhatia, Dinesh K.

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/7928

Dinesh Bhatia is a Professaor of Electrical Engineering and director of the >IDEA Lab His research interests include:

  • Biomedical Systems: Patient Monitoring and Telemedicine
  • Mobile Health
  • Medical Devices and Systems
  • Disease Management Technologies
  • Reconfigurable and Adaptive Computing: Architectures, CAD, and Compilation
  • Interconnection estimation and prediction
  • Architecture and CAD for field-programmable gate arrays (FPGAs)
  • CAD for power aware programmable architectures
  • Theory: Graph theory and its application in VLSI (circuit partitioning, VLSI Design Automation)

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Recent Submissions

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  • Item
    Input-Output Linearization of a Boost Converter with Mixed Load (Constant Voltage Load and Constant Power Load)
    (Institute of Electrical Electronics Engineers Inc, 2018-03-08) Arora, Sameer; Balsara, Poras; Bhatia, Dinesh; 0000-0001-7019-9367 (Arora, S); 0000-0003-1263-787X (Balsara, P); Arora, Sameer; Balsara, Poras; Bhatia, Dinesh
    Power converters and electric motor drives when tightly regulated behave as constant power loads. These loads are different from resistive loads and have destabilizing negative impedance characteristics, which impact a system's stability. A boost converter is intrinsically nonlinear and is a nonminimum phase system at the output voltage with respect to the control input. The linear approximation of this boost converter loaded with a constant power load has a zero and poles in the right half of the s-plane, making the system unstable and very difficult to control. Control techniques that employ some form of system inversion cannot be implemented for a nonminimum phase system. This paper describes a technique to modify the nonminimum phase boost converter to a minimum phase for a constant power load, further implementing the input-output linearization technique to stabilize the system. This paper also provides a methodological analysis of the problem followed by the proposed solution. Furthermore, it verifies the analysis of the proposed solution through simulation and experimental results.

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