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About

Parisa Nikdel is a researcher specializing in intelligent control systems, robotics, and advanced materials, with a focus on shape memory alloys (SMAs) and flexible joint robots. Her most impactful work, "Using Neural Network Model Predictive Control for Controlling Shape Memory Alloy-Based Manipulator" (2013), has garnered 95 citations and introduces a novel control framework for SMA-actuated manipulators, combining neural model predictive control with variable structure controllers to achieve precise, adaptive motion. This contribution is pivotal for applications in soft robotics and biomedical devices, where SMA’s unique properties enable compact, lightweight actuation. Nikdel further advances control theory through her work on Takagi–Sugeno (T-S) fuzzy models for flexible joint robots, as seen in her 2014 paper (33 citations) and 2012 study (12 citations). She integrates Hybrid-Taguchi genetic algorithms and chaos-based optimization to enhance controller stability and performance, addressing critical challenges in robotic flexibility and nonlinear dynamics. Her research bridges theoretical rigor with practical implementation, offering robust solutions for real-world robotic systems. With a citation count exceeding 140, Nikdel’s contributions are recognized for their innovation in intelligent control, making her a notable figure in the intersection of robotics, materials science, and computational intelligence.