Papers
7
Total Citations
54
H-Index
4
About
Muwahida Liaquat is a control systems and robotics researcher whose work spans distributed optimization, multi-agent systems, and nonlinear observer design for robotic applications. Her most impactful contribution, "Discretized Distributed Optimization Over Dynamic Digraphs" (2024, 30 citations), addresses a fundamental challenge in distributed learning and multi-agent coordination by developing a discrete-time optimization algorithm capable of operating over dynamically switching, strongly connected directed networks — a significant advance for real-world mobile systems where network topologies are rarely static. Liaquat has also made notable contributions to cooperative robotics control, particularly in leader-following formation problems for nonholonomic robots under switching network topologies, employing distributed Luenberger observers to achieve robust coordination. Her sustained work on high-gain and cascade high-gain observers for n-link robotic manipulators tackles the practical challenge of peaking phenomena in high-order systems, offering more numerically reliable state estimation under measurement noise and model uncertainties. Her early work on sampled-data output regulation further demonstrates a commitment to bridging theoretical control design with implementable digital systems. Collectively, her research reflects a coherent vision of making autonomous multi-robot and distributed systems more robust, scalable, and practically deployable across dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Discretized Distributed Optimization Over Dynamic Digraphs30 citations · 2024
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- 7Study of Formation Control of Mobile Robots3 citations · 2020