Output Information Based Fault-Tolerant Iterative Learning Control for Dual-Rate Sampling Process with Disturbances and Output Delay

Abstract

For a class of single-input single-output (SISO) dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D) repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs) technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.

Iterative Learning Control for Actuator Fault Uncertain Systems

“…). For a scalar γ > 0, if the F-M model (Equation (19)) is asymptotically stable, and for the zero-boundary condition and any disturbance w(t,k),the system output satisfies Equation…”

“…Therefore, to improve the control performance of the current batch, the ILC algorithm can be combined with the research based on the repeatability and periodicity of the intermittent process. In ILC, the intermittent process can be transformed into corresponding two-dimensional models [17][18][19], and 2D system theory can be applied to break through various of constraints in one-dimensional systems [19]. Therefore, when designing the controller, the control effectiveness can be optimized by iteratively learning the information of the previous batch, and LMI can be applied to solve the parameters of the controller effectively.…”

Maximum likelihood identification of dual‐rate Hammerstein output‐error moving average system

“…In recent years, DR or multi-rate systems have become an extremely active research field. In addition to the lifting technology [9,10], some new technologies for dealing with multirate system problems have emerged, such as the identification method established based on the auxiliary model [11][12][13][14], the polynomial transformation technique [3,15,16], the improved Kalman algorithm [17], and so on. The identification of multi-rate systems has attracted the attention of a large number of scholars.…”

Robust PD-Type Iterative Learning Control of Discrete Linear Repetitive Processes in the Finite Frequency Domain

“…In order to solve the actuator failure problem of discrete linear repetitive processes with convex polyhedral uncertainties, a robust fault-tolerant iterative learning controller is designed by using the parameter-dependent Lyapunov function in reference [11], which guarantees the fault-tolerant stability of the learning process and widens the uncertainty range. Furthermore, in reference [12], a robust fault-tolerant iterative control strategy is studied based on the output feedback information for the dual-rate sampling linear repetitive process with output delay. The stability conditions of the closed-loop system are derived by using the stability theory of linear repetitive process and LMI tools.…”