Multiple Model Predictive Functional Control for Marine Diesel Engine

Abstract

A novel control scheme based on multiple model predictive functional control (MMPFC) is proposed to solve the cumbersome and time-consuming parameters tuning of the speed controller for a marine diesel engine. It combines the MMPFC with traditional PID algorithm. In each local linearization, a first-order plus time delay (FOPTD) model is adopted to be the approximate submodel. To overcome the model mismatches under the load disturbance conditions, we introduce a method to estimate the open-loop gain of the speed control model, by which the predictive multimodels are modified online. Thus, the adaptation and robustness of the proposed controller can be improved. A cycle-detailed hybrid nonlinear engine model rather than a common used mean value engine model (MVEM) is developed to evaluate the control performance. In such model, the marine engine is treated as a whole system, and the discreteness in torque generation, the working imbalance among different cylinders, and the cycle delays are considered. As a result, more reliable and practical validation can be achieved. Finally, numerical simulation of both steady and dynamic performances of the proposed controller is carried out based on the aforementioned engine model. A conventional welltuned PID with integral windup scheme is adopted to make a comparison. The results emphasize that the proposed controller is with stable and adaptive ability but without needing complex and tough parameters regulation. Moreover, it has excellent disturbance rejection ability by modifying the predictive multimodels online.

Speed Control for a Marine Diesel Engine Based on the Combined Linear-Nonlinear Active Disturbance Rejection Control

“…In this paper, only the discrete torque generation process and the final crankshaft dynamic are provided. Else contents of the engine model, such as engine cycle delays, intake and exhaust manifold, intercooler, turbocharger, can refer to the authors' previous work [5].…”

“…For more information about the engine model and the mentioned symbols, refer to [5]. Figure 3 denotes the enlarged plots for the corresponding compared variables within around one engine working cycle.…”

“…Compared with the aviation, rail, and automobile transport, shipping is known as the most energy efficient and environmental friendly classical mode of transport [1]. The energy generated by marine diesel engines is widely used in the domain of ship propulsion [2][3][4][5]. In such application, speed control for the marine main engine becomes a crucial task.…”

Variable Sampling Rate based Active Disturbance Control for a Marine Diesel Engine

“…As can be found in the literature, vast control techniques have been investigated for marine engine speed control. Some of them range from the model-independent methods, such as classical Proportional-Integral-Derivative (PID) control [10], Sliding Model Control (SMC) [2,5], to the model-based approaches, e.g., H ∞ control [11] and Model Predictive Control (MPC) [12,13]. Some others are designed by synthesizing classical PID approach with intelligent algorithms, such as fuzzy technique [14,15].…”

“…Thus, it is necessary to verify the control effect of ADRC by such a model. The advantages of designing a controller by using CA based engine models can be found in some other recent works [12,24,27,39]. In this study, the engine model not only has the traits in [27,39], but also considers the discrete torque generation and cylinder-by-cylinder variation.…”