Confirmation of a Nonlinear Model Predictive Control Strategy Applied to a Permanent Magnet Linear Generator for Wave-Energy Conversion

Author(s):  
Nathan Tom

This paper begins with a brief review of the time-domain equation of motion for a generic floating body. The equation of motion of the floating body was modified to account for the influence of a power-take-off unit (PTO) to predict the hydrodynamic and electromechanical performance of the coupled system. As the damping coefficient is considered the dominant contribution to the PTO reaction force, the optimum non time-varying damping values were first presented for all frequencies, recovering the well-known impedance-matching principle at the coupled resonance frequency. In an effort to further maximize power absorption in both regular and irregular wave environments, nonlinear model predictive control (NMPC) was applied to the model-scale point absorber developed at UC Berkeley. The proposed NMPC strategy requires a PTO unit that could be turned on and off instantaneously, leading, interestingly to electrical sequences where the generator would be inactive for up to 60% of the wave period. In order to validate the effectiveness of this NMPC strategy, an in-house designed permanent magnet linear generator (PMLG) was chosen as the PTO. The time-varying performance of the PMLG was first characterized by dry-bench tests, using mechanical relays to control the electromagnetic conversion process. Following this, the physical set-up was transferred to the wave tank. The on/off sequencing of the PMLG was tested under regular and irregular wave excitation to validate NMPC simulations using control inputs obtained from running the control algorithm offline. Experimental results indicate that successful implementation was achieved and the absorbed power using NMPC was up to 50% greater than the passive system, which utilized no controller. However, after considering the PMLG mechanical-to-electrical conversion efficiency the useful electrical power output was not consistently maximized. To improve output power, a mathematical relation between the efficiency and damping magnitude of the PMLG was inserted in the system model to maximize the electrical power output through continued use of NMPC. Of significance, results from these latter simulations provided a damping time series that was active over a larger portion of the wave period and required the actuation of the applied electrical load connected to the PMLG, rather than a simple on/off type control.

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Xian Du ◽  
Yan-Hua Ma ◽  
Xi-Ming Sun

Abstract A Min-Max structure combined with several linear limit controllers are utilized for conventional aero-engines safety control, which is complex and conservative, therefore a new nonlinear model predictive control strategy is proposed that owns the ability to manage time-varying input/output limits during acceleration/deceleration transient states of aero-engines. Penalty function items are constructed according to the characteristics of input/output limits, and are incorporated in the cost function of online receding horizon optimization for limit management of aero-engines. Considering the large computational burden of nonlinear component-level aero-engine model directly used as prediction model, a piecewise linear model is built to describe the steady-state and dynamic properties of aero-engines and its design process is explained in detail. Further, computational efforts are investigated as control horizon, prediction horizon are varied in the improved nonlinear predictive controller. Particularly, when penalty function items are activated, control performance and computational burden are examined, thus providing guidelines for key parameters tuning. Simulations show two clear results. One is that computational efforts become larger for bigger control horizon or prediction horizon, but it depends more on control horizon than prediction horizon. The other is that the proposed method can handle time-varying input/output limits effectively without resulting in a great increase of computational burden.


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