This brief develops an innovative robust iterative learning control law using the repetitive process setting. The new design is experimentally validated through a comprehensive set of experiments highlighting the capabilities for the position tracking control of a permanent magnet synchronous motor subject to load disturbances in the presence of uncertainties in selected parameters.

This article addresses the problem of input saturation in iterative learning control (ILC), a problem area that has seen relatively little research effort. A new design is developed based on a branch of 2-D systems theory and, in particular, Lyapunov-based stability theory. The resulting design is compared in simulation with an alternative. In the final part of this article, the results of an in-depth experimental investigation of the new designs properties are reported.

Servo-drives have a significant influence on the tracking accuracy of numerically controlled machine tools. It is important to properly choose the structure and gains of a servo-drive control system. This paper presents a tuning method for position and velocity controllers of digital servo-drives. The proposed method allows the controllers’ gain values regardless of controller types (P, PI, PD or PID) to be determined. It takes into account a number of parameters relevant to practical applications, such as the shape of the position error signal and the resolution of the transducer used to measure the angular position of the motor shaft. The controller gains are determined for a parabolic position command signal. A comparison of the influence of both controllers’ types and feed-forward control types on tracking error is also presented. DOI: http://dx.doi.org/10.5755/j01.eee.20.3.2788

This paper presents a design approach of a position controller for permanent magnet synchronous motor (PMSM) servo-drive. Firstly the well know nonlinear mathematical model of PMSM is evaluated to a linear form by introducing new variables. The state space new model presented in rotates ortogonal reference frame is decupled in means of equation in d and q axis. An internal input model have been used to achive zero steady state error for step input and as well as disturbance rejection. The proposed control method is implemented and tested in a 0,6 kW PMSM drive (TMS320F2812-DSP). The experimental test results are consistent with our computer simulation test results and validate the high performance of proposed control method.

This article develops an iterative learning control (ILC) design for a class of multiple-input-multiple-output systems where a distributed heating system is used as a particular example to experimentally validate the design. The class of systems considered is described by a parabolic partial differential equation, which, for control design, is approximated by a finite-dimensional state-space model obtained by applying the method of integro-differential relations combined with a projection approach. In some cases, including the distributed heating system, this approximation may result in a nonminimum phase system and, hence, pose an additional design challenge. In this work, the ILC law is computed in the frequency domain by solving a convex optimization problem, and its performance is evaluated in both simulation and experiment.