Sergey Samokhin

Robustness of the control system in marine engines with respect to its time-varying dynamics has recently become an important research topic. The variation of dynamics, caused primarily by the mechanical wear of components or their faults originating from tough operating condition, can lead to the overall control system instability (or marginal stability, depending on how severe the variation is). The biggest issue is that the marine engines cannot always be fixed fast enough (especially on large cargo vessels, spending hundreds of hours cruising). In this paper, a control adaptation (indirect model-reference adaptive control) is proposed to deal with the engine parameter variation in a way that the original system response is preserved. The stability and robustness of the proposed control system are studied by means of numerical simulations. Finally, the performance of the control concept is validated on the medium-speed diesel engine test bed at constant speed under load transients. Superior performance compared with fixed-parameter proportional-integral control is demonstrated.

It is known that mechanical wear and tear of components of large marine engines throughout their lifetime can cause the engine dynamics to alter. Since traditional control systems with fixed parameters cannot deal with this issue, the engine performance may degrade. In this work, we introduce adaptive control algorithms capable of adapting the control system in order to preserve the engine performance once its dynamics deviate from the nominal ones. Particularly, the direct and indirect model reference adaptation mechanisms are studied. In this work, the case of degraded oxygen sensor is investigated as an example of engine components deterioration throughout its lifetime. The controllers are implemented in Simulink, and their performance is evaluated under both nominal and degraded sensor conditions. Specifically, the sensor degradation is imitated by altering its time-delay. In such conditions, adaptive controllers demonstrate a notable improvement in tracking performance compared to the fixed parameters proportional-integral (PI) controller. Finally, the designed controllers are validated on the hybrid marine engine testbed using dSpace rapid prototyping system.

Exhaust gas recirculation (EGR) has become an integral part of the NO_x emission reduction mechanisms utilized in modern combustion engines. However, capabilities to recirculate the processed gas are oftentimes compromised by the inability to surmount the pressure differential between the intake and exhaust manifolds. The issue is dealt with successfully by the turbocharged EGR system discussed in this article. The increased complexity of such an EGR system requires a multivariable control system in order to achieve the EGR set-point tracking across the desired operating range. In this work, model predictive control is used to naturally incorporate the information about system internal couplings and constraints via the prediction model. The states of the partially observed EGR system required for the feedback control are recovered by using the unscented Kalman filter. Finally, the designed unscented MPC (UMPC) system is validated by numerical simulations.