Resource-aware motion control:feedforward, learning, and feedback

Controllers with new sampling schemes improve motion systems’ performanc

On optimal feedforward and ILC: the role of feedback for optimal performance and inferential control

The combination of feedback control with inverse model feedforward control or iterative learning control is known to yield high performance. The aim of this paper is to clarify the role of feedback in the design of feedforward controllers, with specific attention to the inferential situation. Recent developments in optimal feedforward control are combined with feedback control to jointly optimize a single performance criterion. Analysis and application show that the joint design addresses the specific control objectives. The combined design is essential in control, and in particular in inferential control

Stable inversion of LPTV systems with application in position-dependent and non-equidistantly sampled systems

Many control applications, including feedforward and learning control, involve the inverse of a dynamical system. For nonminimum-phase systems, the response of the inverse system is unbounded. For linear time-invariant (LTI), nonminimum-phase systems, a bounded, noncausal inverse response can be obtained through an exponential dichotomy. For generic linear time-varying (LTV) systems, such a dichotomy does not exist in general. The aim of this paper is to develop an inversion approach for an important class of LTV systems, namely linear periodically time-varying (LPTV) systems, which occur in, e.g. position-dependent systems with periodic tasks and non-equidistantly sampled systems. The proposed methodology exploits the periodicity to determine a bounded inverse for general LPTV systems. Conditions for existence are provided. Themethod is successfully demonstrated in several application cases, including position-dependent and non-equidistantly sampled systems

Feedforward for multi-rate motion control: enhanced performance and cost-effectiveness

In traditional feedback control, a single sampling rate is used for all control loops. Consequently, achieving higher performance by increasing the sampling rate is generally costly. The aim of this paper is to develop a multi-rate control framework to create a breakthrough in the performance/cost trade-off in digital controller implementation. In the proposed approach one of the control loops is implemented at a lower rate of which the feedforward controller is designed through norm-based minimalization of the tracking error in this multi-rate framework. By designing and implementing one of the control loops at a lower rate, the cost is reduced and the multi-rate problem is addressed. Through simulation the adequate performance of the proposed multi-rate approach is demonstrated