Pankaj Kumar Mishra
Papers
1
Total Citations
41
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1
About
Pankaj Kumar Mishra is a leading figure in advanced nonlinear control theory, with a primary focus on adaptive neural-network control for complex, constrained dynamical systems. His most cited work, "Adaptive Neural-Network Control of MIMO Nonaffine Nonlinear Systems With Asymmetric Time-Varying State Constraints" (2019, 41 citations), introduces a groundbreaking robust adaptive barrier Lyapunov function (BLF)-based backstepping controller. This design tackles the formidable challenge of stabilizing interconnected, multi-input-multi-output (MIMO) unknown nonaffine nonlinear systems while respecting asymmetric time-varying (ATV) state constraints—a critical issue in robotics and aerospace applications. By integrating neural networks to handle system uncertainties, Mishra’s approach provides a rigorous yet practical framework for ensuring safety and performance. His contributions have been widely cited by researchers in adaptive control and nonlinear systems, reflecting their impact on both theoretical advancements and real-world implementations. Mishra’s work stands out for its innovative use of BLFs to address nonaffine dynamics, marking him as a key innovator in the field of constrained control systems.
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