Subtopic Deep Dive
Sliding Mode Control in Mobile Robotics
Research Guide
What is Sliding Mode Control in Mobile Robotics?
Sliding Mode Control in Mobile Robotics applies higher-order sliding mode techniques for robust trajectory tracking and stabilization of nonholonomic wheeled mobile robots under model uncertainties and disturbances.
This subtopic focuses on controllers achieving finite-time convergence while reducing chattering in mobile robots. Key methods include terminal sliding surfaces and adaptive neural approximations. Over 2,800 citations across top papers like Yang and Kim (1999, 631 citations) and Chwa (2004, 387 citations).
Why It Matters
Sliding mode control ensures robust performance in uncertain environments, critical for autonomous navigation in cluttered spaces (Hoy et al., 2014, 458 citations). It enables precise trajectory tracking for wheeled robots despite nonholonomic constraints (Yang and Kim, 1999). Applications include unmanned ground vehicles and collision-free path following, improving real-world deployment reliability (Chwa, 2004; Park et al., 2008).
Key Research Challenges
Chattering Reduction
High-frequency switching in sliding mode causes vibrations, limiting practical use in mobile robots. Higher-order modes and non-singular surfaces address this (Zuo, 2014, 530 citations). Adaptive techniques further mitigate it (Park et al., 2008).
Nonholonomic Constraints
Wheeled robots face non-integrable velocity constraints, complicating stabilization. Polar coordinate transformations enable tracking (Chwa, 2004, 387 citations). Backstepping integration helps handle dynamics (Wu et al., 2019).
Model Uncertainties
Unknown disturbances and parameter variations degrade performance. Neural networks adaptively compensate in sliding modes (Park et al., 2008, 283 citations). Fixed-time convergence ensures robustness (Zuo, 2014).
Essential Papers
Nonholonomic mechanical systems with symmetry
Anthony M. Bloch, P. S. Krishnaprasad, Jerrold E. Marsden et al. · 1996 · Archive for Rational Mechanics and Analysis · 687 citations
Sliding mode control for trajectory tracking of nonholonomic wheeled mobile robots
Jongmin Yang, Jong-Hwan Kim · 1999 · IEEE Transactions on Robotics and Automation · 631 citations
Nonholonomic mobile robots have constraints imposed on the motion that are not integrable, i.e., the constraints cannot be written as time derivatives of some function of the generalized coordinate...
Non‐singular fixed‐time terminal sliding mode control of non‐linear systems
Zongyu Zuo · 2014 · IET Control Theory and Applications · 530 citations
This study addresses a fixed‐time terminal sliding‐mode control methodology for a class of second‐order non‐linear systems in the presence of matched uncertainties and perturbations. A newly define...
Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey
Michael Hoy, Alexey S. Matveev, Andrey V. Savkin · 2014 · Robotica · 458 citations
SUMMARY We review a range of techniques related to navigation of unmanned vehicles through unknown environments with obstacles, especially those that rigorously ensure collision avoidance (given ce...
Sliding-Mode Tracking Control of Nonholonomic Wheeled Mobile Robots in Polar Coordinates
D. Chwa · 2004 · IEEE Transactions on Control Systems Technology · 387 citations
This brief proposes a sliding-mode control method for wheeled-mobile robots in polar coordinates. A new sliding-mode control method is proposed for mobile robots with kinematics in two-dimensional ...
Adaptive Neural Sliding Mode Control of Nonholonomic Wheeled Mobile Robots With Model Uncertainty
Bong Seok Park, Sung Jin Yoo, Jin Bae Park et al. · 2008 · IEEE Transactions on Control Systems Technology · 283 citations
This brief proposes an adaptive neural sliding mode control method for trajectory tracking of nonholonomic wheeled mobile robots with model uncertainties and external disturbances. The dynamic mode...
Path-tracking of autonomous vehicles using a novel adaptive robust exponential-like-sliding-mode fuzzy type-2 neural network controller
Hamid Taghavifar, Subhash Rakheja · 2019 · Mechanical Systems and Signal Processing · 135 citations
Reading Guide
Foundational Papers
Start with Bloch et al. (1996, 687 citations) for nonholonomic symmetry foundations, then Yang and Kim (1999, 631 citations) for core sliding mode tracking, followed by Chwa (2004, 387 citations) for polar advancements.
Recent Advances
Study Zuo (2014, 530 citations) for non-singular fixed-time modes, Park et al. (2008, 283 citations) for neural adaptation, and Wu et al. (2019) for fuzzy backstepping hybrids.
Core Methods
Core techniques: terminal sliding surfaces, backstepping integration, adaptive neural approximation, polar coordinate transforms, and fixed-time convergence laws.
How PapersFlow Helps You Research Sliding Mode Control in Mobile Robotics
Discover & Search
Research Agent uses searchPapers and citationGraph to map 600+ citations from Yang and Kim (1999), revealing clusters in nonholonomic tracking; exaSearch uncovers niche fixed-time variants, while findSimilarPapers links Chwa (2004) to polar coordinate extensions.
Analyze & Verify
Analysis Agent applies readPaperContent to extract sliding surface equations from Zuo (2014), verifies finite-time claims via verifyResponse (CoVe) against GRADE B evidence, and runs PythonAnalysis to simulate chattering reduction with NumPy stability checks.
Synthesize & Write
Synthesis Agent detects gaps in chattering-free methods post-2014 via gap detection; Writing Agent uses latexEditText for controller equations, latexSyncCitations for 10+ references, and latexCompile to produce arXiv-ready reports with exportMermaid for phase-plane diagrams.
Use Cases
"Simulate chattering in Yang 1999 sliding mode controller for wheeled robot."
Research Agent → searchPapers → Analysis Agent → readPaperContent + runPythonAnalysis (NumPy plot of switching frequency) → researcher gets stability plot and reduction metrics.
"Write LaTeX section on adaptive SMC for mobile manipulators citing Chen 2013."
Research Agent → citationGraph → Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations + latexCompile → researcher gets formatted subsection with equations and bibliography.
"Find GitHub code for Zuo 2014 non-singular terminal sliding mode."
Research Agent → paperExtractUrls → Code Discovery → paperFindGithubRepo + githubRepoInspect → researcher gets verified MATLAB/Simulink repo with fixed-time controller implementations.
Automated Workflows
Deep Research workflow scans 50+ papers from OpenAlex, chaining searchPapers → citationGraph → structured report on chattering evolution since 1996. DeepScan's 7-step analysis verifies robustness claims in Park et al. (2008) with CoVe checkpoints and Python sims. Theorizer generates novel hybrid backstepping-SMC theory from Wu et al. (2019) and Zuo (2014).
Frequently Asked Questions
What defines Sliding Mode Control in mobile robotics?
It uses discontinuous control to drive system states onto a sliding surface for robust tracking despite uncertainties, applied to nonholonomic wheeled robots (Yang and Kim, 1999).
What are main methods for chattering reduction?
Higher-order and non-singular terminal sliding modes eliminate chattering while ensuring finite-time convergence (Zuo, 2014, 530 citations); adaptive neural methods compensate uncertainties (Park et al., 2008).
Which are key papers?
Yang and Kim (1999, 631 citations) for trajectory tracking; Chwa (2004, 387 citations) for polar coordinates; Zuo (2014, 530 citations) for fixed-time control.
What open problems remain?
Scaling to multi-robot swarms, integrating vision for unknown obstacles, and hardware-efficient fixed-time controllers without singularities persist beyond current works.
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