Multi‐input–multi‐output system experimental validation of model‐free control and virtual reference feedback tuning techniques

Abstract

This study proposes data-driven model-free adaptive control (MFAC), model-free control (MFC) and virtual reference feedback tuning (VRFT) techniques applied to the control of a representative non-linear multi-input-multi-output (MIMO) system represented by the twin rotor aerodynamic system (TRAS). These data-driven techniques are implemented for both a single MIMO controller and two separately designed single-input-single-output controllers running in parallel for azimuth and pitch control. The three techniques are implemented as MFAC and MFC algorithms and as linear controllers tuned by VRFT. The performance of the three data-driven MIMO control system structures is compared systematically on the basis of the experimental results in terms of the values of the sum of mean squared control errors measured on TRAS equipment.

Virtual Reference Feedback Tuning of Model-Free Control Algorithms for Servo Systems

“…The control algorithms specific to MFC, i.e., the MFC algorithms, are usually referred to as intelligent controllers and the most popular ones are built around proportional (P), proportional-integral (PI), or proportional-integral-derivative (PID) controllers, and are called intelligent proportional (iP), intelligent PI (iPI), and intelligent PID (iPID) controllers. The MFC algorithms have been successfully applied to various processes, such as thermal processes [2], glycemia of type-1 diabetes [3], oscillation damping [4], wheeled autonomous vehicles [5], microalgae cultivation [6], experimental greenhouses [7], surface mounted permanent magnet synchronous motor drive systems [8], and twin rotor aerodynamic systems (TRASs) [9,10]. Recent applications of MFC are reported in [11][12][13].…”

“…The main disadvantage of VRFT is that it does not directly guarantee the closed-loop CS stability. The control algorithms specific to VRFT, i.e., the VRFT algorithms, have been applied recently to TRASs [9,10], two-tank systems [21], quadrotors [22], unmanned gyroplanes [23], non-minimum phase systems [24], robotics [25], and power systems [26].…”

“…Building upon the previous discrete-time implementations of MFC reported in [1][2][3][4][5][6][7][8][9][10][11][12][13] and the mixed MFC-VRFT approach applied to TRASs in [10], this paper proposes a thorough experimental investigation of the new approach, spanning several MFC structures and comparisons with other model-based and model-free tuned controller structures. The main advantages of the proposed approach with respect to the state-of-the-art are:…”

“…-As shown in the applications of MFC algorithms [1][2][3][4][5][6][7][8][9][10][11][12][13], which have mainly achieved the discrete-time implementation of iP, iPI, and iPID controllers, the stability around a reference trajectory is obtained by appropriate gain tuning. -It can be easily generalized to other model-free control techniques.…”

“…The main contributions of this paper with the current literature in the field [1][2][3][4][5][6][7][8][9][10][11][12][13] are: -The mixed MFC-VRFT approach is applied here to an MSS and is experimentally validated by real-time results. -Three different MFC structures are tuned in this paper using the new approach in order to investigate how the controller structure complexity influences the CS performance.…”