A fuzzy logic feedback filter design tuned with PSO for L1 adaptive controller

TL;DR

This paper introduces a fuzzy logic feedback filter for L1 adaptive controllers, tuned online with Particle Swarm Optimization to enhance robustness and adaptation speed in nonlinear systems.

Contribution

It proposes a novel fuzzy rule-based online tuning method for filter coefficients in L1 adaptive control, optimized with PSO for improved performance.

Findings

Enhanced control performance in nonlinear systems

Effective online tuning of filter coefficients

Robustness and adaptation speed improved

Abstract

L1 adaptive controller has been recognized for having a structure that allows decoupling between robustness and adaption owing to the introduction of a low pass filter with adjustable gain in the feedback loop. The trade-off between performance, fast adaptation and robustness, is the main criteria when selecting the structure or the coefficients of the filter. Several off-line methods with varying levels of complexity exist to help finding bounds or initial values for these coefficients. Such values may require further refinement using trial-and-error procedures upon implementation. Subsequently, these approaches suggest that once implemented these values are kept fixed leading to sub-optimal performance in both speed of adaptation and robustness. In this paper, a new practical approach based on fuzzy rules for online continuous tuning of these coefficients is proposed. The fuzzy controller is optimally tuned using Particle Swarm Optimization (PSO) taking into accounts both the tracking error and the controller output signal range. The simulation of several examples of systems with moderate to severe nonlinearities demonstrate that the proposed approach offers improved control performance. Keywords: Fuzzy logic control, single-objective, multi-objective particle swarm optimization, L1 Adaptive control, fuzzy L1 adaptive controller, L1 fuzzy adaptive control, L1 fuzzy adaptive controller, fuzzy L1 adaptive control, Filter tuning, Fuzzy membership function tuning, optimal, optimal tuning, Fuzzy membership function optimization, Robustness, Adaptation, multi-input multi-output, single-input single-output, estimate, PSO, FLC, nonlinear, adaptive, online, off-line, Fuzzy adaptive controller, Fuzzy adaptive control, single input single output, multi input multi output, SISO, MIMO, robust, uncertain, uncertain nonlinear system, disturbance, unknown, Adaptive Fuzzy Control Design, stable.