M. Taherkhorsandi
University of Guilan, The University of Texas at San Antonio
Papers
7
Total Citations
193
H-Index
7
About
M. Taherkhorsandi is a control systems researcher whose work sits at the intersection of robotics, intelligent control, and evolutionary optimization. Best known for pioneering contributions to biped robot locomotion control, Taherkhorsandi has consistently advanced the design of robust, adaptive controllers capable of managing the complex, nonlinear dynamics inherent in bipedal walking. His most influential work, "Optimal Robust Sliding Mode Tracking Control of a Biped Robot Based on Ingenious Multi-Objective PSO" (2013, 68 citations), introduced a landmark framework combining sliding mode control with particle swarm optimization to achieve reliable trajectory tracking without exhaustive manual parameter tuning. Extending this foundation, his research has embraced hybrid methodologies — merging PID, sliding mode, and fuzzy logic frameworks — to tackle MIMO uncertain and chaotic systems, earning an additional 47 citations for a 2016 adaptive robust PID study. Across multiple Pareto-optimal design studies, Taherkhorsandi has systematically benchmarked genetic algorithms, NSGA-II, and multi-objective PSO variants, offering the control community valuable comparative insights. With a cumulative citation profile exceeding 190 references, his body of work represents a sustained and impactful contribution to intelligent, optimization-driven control of autonomous robotic systems.
Research Focus
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Top Papers
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