Computed torque control of fully-actuated nondeterministic multibody systems

Sahand Sabet, Mohammad Poursina

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Multibody dynamics plays a key role in the modeling, simulation, design, and control of many engineering problems. The dynamics of these complex systems can be highly sensitive to uncertainty. In this paper, the method of Polynomial Chaos Expansion (PCE) is extended and integrated with Computed Control Torque Law (CTCL) to model and control fully-actuated nondeterministic multibody systems. PCE provides an efficient mathematical formulation to introduce and propagate uncertainty through the system’s dynamics by compactly projecting each stochastic response output and random input onto a space of appropriate independent orthogonal polynomial base functions. In this paper, a new mathematical formulation is further generated to express CTCL in the PCE scheme. The PCE-based CTCL presented is able to overcome the system’s nonlinearities by using feedback linearization to evaluate generalized driving forces, thus making the nondeterministic multibody system follow the desired trajectory. Herein, this method is applied to control a fully-actuated four-degree-of-freedom Selective Compliance Assembly Robot Arm (SCARA) with multiple uncertainties in the system parameters. The comparison between the time efficiency and accuracy of the PCE-based CTCL and the traditional Monte Carlo method indicates that PCE can provide the desired accuracy in a more time effective manner for some engineering problems.

Original languageEnglish (US)
Pages (from-to)1-19
Number of pages19
JournalMultibody System Dynamics
DOIs
StateAccepted/In press - May 29 2017

Keywords

  • Computed torque control law
  • Control
  • Fully-actuated multibody systems
  • Generalized driving force
  • Polynomial chaos expansion
  • Uncertainty analysis

ASJC Scopus subject areas

  • Modeling and Simulation
  • Aerospace Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Control and Optimization

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