Run-to-Run Adaptive Nonlinear Feedforward Control of Electromechanical Switching Devices

TL;DR

The paper addresses the challenge of achieving fast and accurate control for electromechanical switching devices when real-time position feedback is impractical. It introduces a two-block approach that combines a differential-flatness-based feedforward controller with a run-to-run adaptation that updates feedforward parameters across repetitive operations using a performance cost. Through simulations and real-relay experiments, the method demonstrates substantial reductions in impact velocity during soft landing, without requiring real-time sensing. The work enables robust, high-speed control of repetitive mechatronic systems where traditional feedback is unavailable, with potential applicability to a broad class of electromechanical switches and actuators.

Abstract

Feedforward control can greatly improve the response time and control accuracy of any mechatronic system. However, in order to compensate for the effects of modeling errors or disturbances, it is imperative that this type of control works in conjunction with some form of feedback. In this paper, we present a new adaptive feedforward control scheme for electromechanical systems in which real-time measurements or estimates of the position and its derivatives are not technically or economically feasible. This is the case, for example, of commercial electromechanical switching devices such as solenoid actuators. Our proposal consists of two blocks: on the one hand, a feedforward controller based on differential flatness theory; on the other, an iterative adaptation law that exploits the repetitive operation of these devices to modify the controller parameters cycle by cycle. As shown, this law can be fed with any available measurement of the system, with the only requirement that it can be processed and converted into an indicator of the performance of any given operation. Simulated and experimental results show that our proposal is effective in dealing with a long-standing control problem in electromechanics: the soft-landing control of electromechanical switching devices.

Figures (6)

• Figure 1: Schematic representation of single-coil reluctance actuators
• Figure 2: Control diagram. The superscript $n$ denotes variables of the $n$th operation. The voltage signal $u_\mathrm{d}$ is computed by the feedforward controller as a function of the desired position trajectory $z_\mathrm{d}$ and its derivatives. The run-to-run adaptation law uses the operation cost $J$---computed using the system measurable output $y$---to update the parameter vector $p$ of the feedforward controller only once per operation
• Figure 3: Desired soft-landing trajectory (general form)
• Figure 4: Simulation results. Cost as a function of the number of switching operations. The graph shows the median ($p_{50}$) and the 10th and 90th percentiles ($p_{10}$ and $p_{90}$, respectively) of the distribution of values obtained for the 10 000 simulated experiments. The cost without control is also represented
• Figure 5: Simulation results. Parameter values as a function of the number of switching operations. The graphs show the median ($p_{50}$) and the 10th and 90th percentiles ($p_{10}$ and $p_{90}$, respectively) of the distribution of values obtained for the 10 000 simulated experiments. The nominal values are also represented