Research

Systems and Control

Department of Electrical Engineering  ·  1 research labs  ·  4 faculty members

Control TheoryOptimal ControlModel Predictive ControlRobust & Adaptive ControlMulti-Agent SystemsNetworked Control SystemsEvent-Triggered ControlData-Driven ControlAutonomous Motion PlanningCyber-Physical SecurityFault Detection & DiagnosisState Estimation & FilteringStatistical Process ControlAlarm ManagementSystem IdentificationStatistical Learning TheoryCompressed SensingMachine LearningComputational BiologyMicrogrid & PV ControlMarine Robotics
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Research Laboratories

The stream's experimental and theoretical work is carried out across the laboratories below. Select a laboratory to jump to its faculty and research areas.

EEL13 Dynamics and Control Lab 2 faculty members

Laboratories in Detail

Dynamics and Control Lab

Room EEL13 2 faculty members

Dr. Ketan Detroja

Research Interests

Works on advanced process control and monitoring, spanning fault detection and diagnosis, statistical process control, state estimation, and model predictive control. Research includes nonlinear process fault detection, batch process monitoring, alarm management, and efficient algorithms for pattern matching and diagnosis, alongside interests in system identification and cooperative control.

Dr. Vishal Sawant

Research Interests

Works on control systems for networked and autonomous applications, spanning multi-agent systems, optimal and structured controller design, autonomous motion planning, and cyber-physical security. Recent work includes data-driven controller synthesis and the co-design of event-triggered and sparse control for resource-aware networked control systems.

Other Faculty

2 faculty members

Emeritus, distinguished, adjunct and practice faculty contributing to the stream without a separately listed laboratory.

Prof. Bidyadhar Subudhi

Research Interests

Works on system and control theory, including robust and adaptive control, estimation and filtering, and machine learning for adaptive systems. Application areas span the control of photovoltaic systems and microgrids — adaptive grid synchronisation, maximum power point control, and distributed microgrid control — together with active power filtering, electric vehicles, and marine robotics including autonomous underwater vehicles.

Prof. Mathukumalli Vidyasagar

Research Interests

Works on system and control theory at the intersection of engineering and mathematics, together with statistical learning theory and compressed sensing. Research has produced foundational results on how machines learn from examples, with recent work applying machine-learning methods to computational biology and the design of personalised cancer therapy.

Postgraduate Courses — Current Semester

M.Tech and Ph.D. courses offered by the stream during August – November 2026. Select a course for its detail page.

CodeCourse NameType
EE5540Optimal ControlCore