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About

Neha Kapoor is a researcher specializing in intelligent control systems, robotic manipulator control, and computational optimization techniques. Her work sits at the intersection of classical control theory and advanced soft computing methodologies, with a particular focus on developing robust, high-performance controllers for nonlinear robotic systems. Kapoor's most influential contribution is her development of the Fuzzy Sliding Mode Controller (FSMC) with global stabilization and a novel exponential dynamic sliding function incorporating PID, which has garnered 18 citations and significantly advanced trajectory control for robotic manipulators. Her broader body of work systematically addresses key challenges in manipulator control — including chattering reduction, error convergence, and parameter tuning — through innovative hybrid approaches that combine Sliding Mode Control (SMC), fuzzy logic, Particle Swarm Optimization (PSO), Support Vector Machines (SVM), and neural networks. Notable among her contributions is the Evolutionary Optimized Neural Network (EONN) framework and PSO-tuned classical controllers, demonstrating her commitment to bridging theoretical rigor with practical applicability. Across seven highly cited publications between 2013 and 2016, Kapoor has accumulated over 70 citations, establishing herself as a productive contributor to intelligent robotics and control engineering research.