FFTSMC with Optimal Reference Trajectory Generated by MPC in Robust Robotino Motion Planning with Saturating Inputs

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

Mobile robots are remarkable cases of highly developed technology and systems. The robot community has developed a complex analysis to meet the increased demands of the control challenges pertaining to the movement of robot. An approach using Explicit Model Predictive Control (MPC) in combination with Sliding Mode Control (SMC) in the context of a decoupling controller is proposed. The MPC works in the outer loop of the control and is used to generate the unique optimal reference trajectory. The generated reference resulting from the convex optimisation problem is to be tracked by the SMC. The SMC works in the inner loop of the proposed control strategy to compensate the nonlinearities. MPC is used over the more common PID strategy as it is able to handle saturation with better tracking and error. Implementation of three possible different SMC strategies such as classical SMC, Finite Time Sliding Mode Control (FTSMC), and Fast Finite Time Sliding Mode Control (FFTSMC) using Matlab/Simulink shows promising results even in the presence of external disturbances. In particular, in the case of FFTSMC, the paper exhibits a Proposition and a Theorem. In particular, the Theorem gives sufficient condition to avoid saturating inputs, while in the meantime preserving asymptotic stability. We were able to validate the approach using simulations to compare outcomes and tune to optimal results.

Original languageEnglish
Title of host publication2021 American Control Conference (ACC)
Number of pages8
Place of PublicationPiscataway
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication date25.05.2021
Pages1470-1477
Article number9482876
ISBN (print)978-1-7281-9704-3
ISBN (electronic)978-1-6654-4197-1, 978-1-6654-4198-8
DOIs
Publication statusPublished - 25.05.2021
EventAmerican Control Conference - ACC 2021 - Virtual, New Orleans, United States
Duration: 25.05.202128.05.2021
https://acc2021.a2c2.org/

    Research areas

  • Holonomic mobile robots, Lyapunov approach, Model predictive control, Robotino, saturating inputs, Sliding mode control

Recently viewed

Publications

  1. On the Nonlinearity Compensation in Permanent Magnet Machine Using a Controller Based on a Controlled Invariant Subspace
  2. Analysis and Implementation of a Resistance Temperature Estimator Based on Bi-Polynomial Least Squares Method and Discrete Kalman Filter
  3. Different complex word problems require different combinations of cognitive skills
  4. Control of a Sun Tracking Robot Based on Adaptive Sliding Mode Control with Kalman Filtering and Model Predictive Control
  5. A simple fuzzy controller for robot manipulators with bounded inputs
  6. Analysis of semi-open queueing networks using lost customers approximation with an application to robotic mobile fulfilment systems
  7. Anomaly detection in formed sheet metals using convolutional autoencoders
  8. Anatomy of Haar Wavelet Filter and Its Implementation for Signal Processing
  9. Framework for setting up and operating biobanks
  10. The Use of Factorization and Multimode Parametric Spectra in Estimating Frequency and Spectral Parameters of Signal
  11. A Multilevel CFA-MTMM Model for Nested Structurally Different Methods
  12. Identification of structure-biodegradability relationships for ionic liquids - clustering of a dataset based on structural similarity
  13. Semantic Parsing for Knowledge Graph Question Answering with Large Language Models
  14. Control of the inverse pendulum based on sliding mode and model predictive control
  15. Introducing a multivariate model for predicting driving performance
  16. Reading and Calculating in Word Problem Solving
  17. Enhancing the Building Information Modeling Lifecycle of Complex Structures with IoT
  18. Simultaneous Constrained Adaptive Item Selection for Group-Based Testing
  19. 'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY
  20. Trajectory-based computational study of coherent behavior in flows
  21. Inversion of fuzzy neural networks for the reduction of noise in the control loop
  22. Clustering Hydrological Homogeneous Regions and Neural Network Based Index Flood Estimation for Ungauged Catchments
  23. XOperator - An extensible semantic agent for instant messaging networks