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Robust Model-Free Control Framework with Safety Constraints for a Fully Electric Linear Actuator System

Mehdi Heydari Shahna, Pauli Mustalahti, Jouni Mattila

TL;DR

This work addresses robust, safety-constrained control of a PMSM-powered electromechanical linear actuator (EMLA) subject to non-idealities and modeling uncertainties. It introduces a trajectory-setting reference combined with a dual robust subsystem-based barrier Lyapunov function (DRS-BLF) controller, plus saturation-based control signal limiting, to achieve uniform exponential stability under disturbances. Gains are automatically tuned via the Jaya optimization algorithm using an objective based on tracking errors, and current/motion tasks are handled in a unified framework. Experimental results on a PMSM-driven EMLA demonstrate notable improvements over PID control in position and velocity tracking, torque economy, and convergence speed, validating practical applicability for safely actuated heavy machinery.

Abstract

This paper introduces a novel model-free control strategy for a complex multi-stage gearbox electromechanical linear actuator (EMLA) system, driven by a permanent magnet synchronous motor (PMSM) with non-ideal ball screw characteristics. The proposed control approach aims to (1) manage user-specified safety constraints, (2) identify optimal control parameters for minimizing tracking errors, (3) ensure robustness, and (4) guarantee uniformly exponential stability. First, this paper employs a trajectory-setting interpolation-based algorithm to specify the piecewise definition of a smooth and jerk-bounded reference trajectory. Then, a dual robust subsystem-based barrier Lyapunov function (DRS-BLF) control is proposed for the PMSM-powered EMLA system to track the reference motions, guaranteeing user-specified safety related to constraints on system characteristics and alleviating control signal efforts. This methodology guarantees robustness and uniform exponential convergence. Lastly, optimal control parameter values are determined by customizing a swarm intelligence technique known as the Jaya (a term derived from the Sanskrit word for `victory') algorithm to minimize tracking errors. Experimental results validate the performance of the DRS-BLF control.

Robust Model-Free Control Framework with Safety Constraints for a Fully Electric Linear Actuator System

TL;DR

This work addresses robust, safety-constrained control of a PMSM-powered electromechanical linear actuator (EMLA) subject to non-idealities and modeling uncertainties. It introduces a trajectory-setting reference combined with a dual robust subsystem-based barrier Lyapunov function (DRS-BLF) controller, plus saturation-based control signal limiting, to achieve uniform exponential stability under disturbances. Gains are automatically tuned via the Jaya optimization algorithm using an objective based on tracking errors, and current/motion tasks are handled in a unified framework. Experimental results on a PMSM-driven EMLA demonstrate notable improvements over PID control in position and velocity tracking, torque economy, and convergence speed, validating practical applicability for safely actuated heavy machinery.

Abstract

This paper introduces a novel model-free control strategy for a complex multi-stage gearbox electromechanical linear actuator (EMLA) system, driven by a permanent magnet synchronous motor (PMSM) with non-ideal ball screw characteristics. The proposed control approach aims to (1) manage user-specified safety constraints, (2) identify optimal control parameters for minimizing tracking errors, (3) ensure robustness, and (4) guarantee uniformly exponential stability. First, this paper employs a trajectory-setting interpolation-based algorithm to specify the piecewise definition of a smooth and jerk-bounded reference trajectory. Then, a dual robust subsystem-based barrier Lyapunov function (DRS-BLF) control is proposed for the PMSM-powered EMLA system to track the reference motions, guaranteeing user-specified safety related to constraints on system characteristics and alleviating control signal efforts. This methodology guarantees robustness and uniform exponential convergence. Lastly, optimal control parameter values are determined by customizing a swarm intelligence technique known as the Jaya (a term derived from the Sanskrit word for `victory') algorithm to minimize tracking errors. Experimental results validate the performance of the DRS-BLF control.
Paper Structure (17 sections, 60 equations, 7 figures, 2 tables, 2 algorithms)

This paper contains 17 sections, 60 equations, 7 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Background of Fully Electric Actuation Systems
  3. Control Challenges and Motivations of the Paper
  4. Non-ideal configurations and modeling errors
  5. User-specified safety constraints
  6. Tuning control parameters
  7. Literature review
  8. Paper Contributions and Organization
  9. Pmsm-powered Emla Modeling
  10. Mathematical EMLA Model
  11. Mathematical Model of Voltage and Torque Constraints
  12. Jerk-bounded Trajectory Planning
  13. Drs-blf Control Framework
  14. Uniformly Exponential Stability Analysis
  15. Optimization Of Drs-blf Control Parameters
  16. ...and 2 more sections

Figures (7)

  • Figure 1: Configuration of the EMLA system driven by a PMSM heydari2024robust.
  • Figure 2: Cubic and quantic polynomials under the same conditions.
  • Figure 3: Interconnections of the EMLA mechanism (blue boxes), implemented by motion planning (yellow boxes) and DRS-BLF control (orange boxes).
  • Figure 4: The studied PMSM-driven EMLA under a pushing load generated by an external linear hydraulic actuator.
  • Figure 5: (a) Minimizing objective function, (b) load force generated by a hydraulic actuator, (c) torque generated by the EMLA.
  • ...and 2 more figures