An iterative learning control method is proposed to achieve precise tracking control and end-point vibration suppression of a flexible manipulator system. The learning is done in a feedback configuration with collocated PD control and the learning law updates the feedforward input from the error of the previous trial. Simulation results of the response of the manipulator with the controller are...

A wet-plate clutch (Fig. 1) is a mechanical device that transmits torque from its input axis to its output axis by means of friction. The input axis of the clutch is connected to a drum, which is a hollow cylinder with grooves on the inside. A first set of friction plates (clutch plates) with external toothing that can slide in those grooves are pressed against a second set of friction plates (...

In this paper, an iterative learning control method based on the recognition, response, and memory mechanism of immune system (IRRM-ILC) is proposed. According to the immunological recognition, response, and memory processes, several new components are designed and then combined with the conventional ILC. The proposed IRRM-ILC controller can mitigate the disturbances by detecting, identifying, ...

The area if Iterative Learning Control (ILC) has great potential for applications to systems with a naturally repetitive action where the transfer of data from repetition (trial or iteration) can lead to substantial improvements in tracking performance. There are several serious issues arising from the "2D" structure of ILC and a number of new problems requiring new ways of thinking and design....

We derive frequency-domain criteria for the convergence of linear iterative learning control (ILC) on finite-time intervals that are less restrictive than existing ones in the literature. In particular, the former can be used to establish the convergence of ILC in certain cases where the latter are violated. The results cover ILC with non-causal filters and provide insights into the transient b...

This paper presents iterative learning control (ILC) schemes for batch-varying references. Generally, reference or target trajectory must be identical for all iterations to implement the ILC. However, references can be changed in dynamic systems such as robotics and chemical processes according to cycle or batch. ILC schemes for batch-varying references are proposed in three forms which are inv...

A Learning Model Predictive Controller (LMPC) for iterative tasks is presented. The controller is referencefree and is able to improve its performance by learning from previous iterations. A safe set and a terminal cost function are used in order to guarantee recursive feasibility and nonincreasing performance at each iteration. The paper presents the control design approach, and shows how to r...

Extracting projectile’s optimal fitting drag coefficient curve Cdf from radar measured velocity data is considered as an optimal tracking control problem (OTCP) where Cdf is regarded as a virtual control function while the radar measured velocity data are taken as the desired output trajectory to be optimally tracked. With a three-degree of freedom (DOF) point mass trajectory prediction model, ...