Multi-loop Model Reference Adaptive PID Control for Fault-Tolerance

Abstract

This study demonstrates an application of multiloop Model Reference Adaptive Control (MRAC) structure for enhancement of fault tolerance performance of closed-loop PID control systems. The presented multi-loop MRAC-PID control structure can be used to transform a conventional PID control system to an adaptive control system by combining an outer adaptation loop. This study shows that the proposed control structure can improve fault tolerance and fault detection performance of the existing closed-loop PID control systems without modifying any coefficients of PID controllers, and this asset is very useful for increasing robust control performance of the existing industrial control systems. This advantage originates from the reference input shaping technique that is implemented to combine adaptation and control loops. Numerical and experimental studies are presented to illustrate an application of the MRAC-PID control structure for rotor control applications.

Multi-Loop Model Reference Proportional Integral Derivative Controls: Design and Performance Evaluations

“…The ML-MR PID-MIT control structure has been proposed to enhance the robust control performance of existing closed loop control systems. Its application has been discussed in several works [25][26][27][28]. This structure is essentially composed of two hierarchical control loops: the inner loop is a classical PID control loop that is a stable and well-tuned control loop, while the outer loop is a adaptation loop that performs the MIT rule.…”

“…By using it in Equation (5), the MIT rule for the update of the adaptation coefficient θ to minimize cost function J is obtained as [25,26,28]:…”

“…which is implemented in the outer loop in Figure 1 [25,26,28]. Application of ML-MR PID-MIT control for the existing control loop was defined as follows [25,26,28]:…”

“…The topic of multi-loop control involves a wide variety of control systems that employ multi-loop control structures, including cascaded control loops [11,12], multi-input multi-output control systems [13], use of additional control loops for performance improvements [14,15], direct model reference control based on output matching [16,17], direct model reference adaptive control with online controller tuning [5][6][7][8][9][10], model reference adaptive control based on Massachusetts Institute of Technology (MIT) rule [18][19][20][21][22][23], backstepping-based adaptive PID control [24], and hierarchical ML-MR adaptive control [25][26][27][28]. The current study investigates several configurations of hierarchical ML-MR adaptive control structures.…”

“…There is a need for further research efforts to establish design methodologies and reveal some practical benefits and drawbacks. Therefore, this study aims to investigate the benefits and drawbacks of ML-MR PID-MIT control [25,28] and addresses design and performance improvement problems in ML-MR structures. To this end, this paper revisits recent multi-loop model reference adaptive PID control techniques, and analytical tuning and performance issues are considered.…”