Economic Model Predictive Control and Applications for Diesel Generators

Broomhead, Timothy; Manzie, Chris; Hield, Peter; Shekhar, Rohan C.; Brear, Michael J.

doi:10.1109/tcst.2016.2574758

Cited by 40 publications

(24 citation statements)

References 43 publications

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“…However, the constraint tightening (CT) approach, in which the constraints are systematically tightened and a margin is reserved along the horizon to correct for errors due to uncertainties [18], does not incur additional computational load when compared to the conventional MPC. In [19], a CT-MPC formulation is proposed for diesel generators in power tracking applications. In both [17] and [19], the number of tuning parameters remain the same as in conventional MPC, requiring a significant effort to achieve the desired output time domain characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…In [19], a CT-MPC formulation is proposed for diesel generators in power tracking applications. In both [17] and [19], the number of tuning parameters remain the same as in conventional MPC, requiring a significant effort to achieve the desired output time domain characteristics. Furthermore, as in [20], it might be infeasible to provide robustness guarantees with a large disturbance set because of lack of control authority to reject the disturbances by the end of the horizon in robust MPC formulations.…”

Section: Introductionmentioning

confidence: 99%

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Fast Calibration of a Robust Model Predictive Controller for Diesel Engine Airpath

Sankar

Shekhar

Manzie

et al. 2020

IEEE Trans. Contr. Syst. Technol.

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A significant challenge in the development of control systems for diesel airpath applications is to tune the controller parameters to achieve satisfactory output performance, especially whilst adhering to input and safety constraints in the presence of unknown system disturbances. Model-based control techniques, such as model predictive control (MPC), have been successfully applied to multivariable and highly nonlinear systems, such as diesel engines, while considering operational constraints. However, efficient calibration of typical implementations of MPC is hindered by the high number of tuning parameters and their non-intuitive correlation with the output response. In this paper, the number of effective tuning parameters is reduced through suitable structural modifications to the controller formulation and an appropriate redesign of the MPC cost function to aid rapid calibration. Furthermore, a constraint tightening-like approach is augmented to the control architecture to provide robustness guarantees in the face of uncertainties. A switched linear time-invariant MPC strategy with recursive feasibility guarantees during controller switching is proposed to handle transient operation of the engine. The robust controller is first implemented on a high fidelity simulation environment, with a comprehensive investigation of its calibration to achieve desired transient response under step changes in the fuelling rate. An experimental study then validates and highlights the performance of the proposed controller architecture for selected tunings of the calibration parameters for fuelling steps and over drive cycles.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fast Calibration of a Robust Model Predictive Controller for Diesel Engine Airpath

Sankar

Shekhar

Manzie

et al. 2020

IEEE Trans. Contr. Syst. Technol.

Self Cite

View full text Add to dashboard Cite

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“…Furthermore, speed and load of the marine main engine are strongly affected by numerous other external aspects, such as the weather in the sea and the surface condition of the sea [2,8]. Attempts have been made on the basis of variable control method, such as conventional PID method [9], sliding mode control (SMC) [2], ∞ control [10], 2 Mathematical Problems in Engineering active disturbance rejection control (ADRC) [11], fuzzy control [5], and model predictive control (MPC) [12].…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, ∞ control and MPC techniques not only rely on exact mathematical model, but also require high-performance processor to execute the complex matrix computation. As shown in [12], the MPC method was carried out with the help of two 900-MHz IMB PPC processors, which actually cannot be accepted commercially. Despite the fact that there exists computationally efficient MPC algorithm with online linearization and quadratic optimization (e.g., [13][14][15]), where the online computational requirement is acceptable, such computational simplicity is generally realized by sacrificing the control performance as the linear approximation is invalid when the system state and input deviate far away from where they are linearized.…”

Section: Introductionmentioning

confidence: 99%

Multiple Model Predictive Functional Control for Marine Diesel Engine

Wang

Liu

et al. 2018

Mathematical Problems in Engineering

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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.

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“…These days the heating systems which use several low-power boilers are more popular than using only a single boiler (Broomhead et al, 2017). This article describes a heating system that is used in one particular private home sector in Latvia.…”

Section: Introductionmentioning

confidence: 99%

Practical Validation of Economic Efficiency Modelling Method for Multi-Boiler Heating System

Jurenoks

Jurenoka

Novickis

2017

Journal of Information Systems Engineering & Management

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In up-to-date conditions information technology is frequently associated with the modelling process, using computer technology as well as information networks. Statistical modelling is one of the most widespread methods of research of economic systems. The selection of methods of modelling of the economic systems depends on a great number of conditions of the researched system. Modelling is frequently associated with the factor of uncertainty (or risk), who's description goes outside the confines of the traditional statistical modelling, which, in its turn, complicates the modelling which, in its turn, complicates the modelling process. This article describes the modelling process of assessing the economic efficiency of a multi-boiler adaptive heating system in real-time systems which allows for dynamic change in the operation scenarios of system service installations while enhancing the economic efficiency of the system in consideration.

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Economic Model Predictive Control and Applications for Diesel Generators

Cited by 40 publications

References 43 publications

Fast Calibration of a Robust Model Predictive Controller for Diesel Engine Airpath

Fast Calibration of a Robust Model Predictive Controller for Diesel Engine Airpath

Multiple Model Predictive Functional Control for Marine Diesel Engine

Practical Validation of Economic Efficiency Modelling Method for Multi-Boiler Heating System

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