A Comparison Between MPC and Optimal PID Controllers: Case Studies

Salem, Farhan A.; Mosaad, Mohamed I.

doi:10.1049/cp.2015.1607

Cited by 35 publications

(26 citation statements)

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“…Finite control set MPC (FCS-MPC) is the most frequently used among MPC controls due to its simplicity and high accuracy [7]. MPC is used in various applications including load frequency control for dynamic performance improvement under various disturbances and many applications in electrical drives (speed/position/torque control, torque ripple reduction, fieldoriented control) [8]. VSI with LC filters is widely used in power supplies for high-quality output, which is also the future application in an embedded network of electrical aircraft [9].…”

Section: Nomenclature Abbreviationsmentioning

confidence: 99%

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

et al. 2020

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Microgrids being an important entity in the distribution system, and to get their full advantages by incorporating maximum distributed generation, standalone hybrid renewable energy systems (HRESs), being environmentally-safe and economically-efficient, are considered as the promising solution to electrify remote areas where the grid power is not available. In this work, a techno-economic investigation with an optimal design of HRES is presented to fulfill the domestic electricity need for a residential area of the Sherani district in the Province of Baluchistan, Pakistan. Nine case studies based on PV/wind/diesel/battery are analyzed based on net present cost (NPC), cost of energy (COE), and emission to decide the feasible solution. HOMER tool is utilized to accomplish modeling and simulation for economic analysis and optimal sizing. Simulation results demonstrated that HRES with PV-wind-battery is the most viable option for the specified area, and the optimal sizing of components are also obtained with $ 28,620 NPC and $ 0.311/kWh COE which shows 81.65 % reduction in cost and 100 % preserving in toxic emission while fulfilling 100 % energy demand with 67.3 % of excess energy. Furthermore, MATLAB/Simulink modeling for the optimally designed system is built for technical analysis while its effectiveness is proved by keeping dc and ac buses voltage constant, safe operating range of battery state of charge (SOC) with active power balance between HRES components, as well as efficient ac voltage quality, regardless of generation disturbances and load fluctuations. The output signal has total harmonic distortion (THD) of 0.30 % as compared to 5.44 % with the conventional control scheme. The novelty lies in the sequential application of both HOMER and MATLAB simulations of the proposed HRES model and validation of the proposition for the studied area; by using and implementing model predictive control (MPC) of a reconfigurable inverter. WT

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Section: Nomenclature Abbreviationsmentioning

confidence: 99%

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

et al. 2020

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“…Furthermore, as the indices in steady state speed fluctuation and time-multiplied absolute error can indicate the steady state traits and the indices in setting time and integral absolute error represent the dynamic characteristics [50], it is can be observed from Figures 10, 12, 13, and 14 that the same color lines marked with squares are clearly below the lines marked with stars. Hence, it is evident that the MMPFC-PID controller has better steady and dynamic performances in all the tested processes.…”

Section: Speed Tracking Performance Undermentioning

confidence: 97%

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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“…In general, in the last decades, MPC and NMPC dominate the process industry for a large variety of applications [19]. Critical discussions, theoretical advantages, and quantitative results of using MPC and NMPC over the classical methodologies, like a PID-based controller, can be found in [20], [21], [22, Section 1.3]. Therefore, the use of NMPC over the classical control approaches allow the possibility to explicitly include the slipping conditions and saturation of the actuators within the control design.…”

Section: State Of the Artmentioning

confidence: 99%

Nonlinear Model Predictive Control for the Stabilization of a Wheeled Unmanned Aerial Vehicle on a Pipe

Zhao

Ruggiero

Fontanelli

et al. 2019

IEEE Robot. Autom. Lett.

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This letter addresses the task of stabilizing a wheeled unmanned aerial vehicle on a pipe, which is an emerging application in oil and gas facilities for nondestructive measurements. After the derivation of the dynamic model of the system, a discrete-time nonlinear model predictive controller is designed over a finite horizon. The analysis of the asymptotic stability of the designed controller is carried out. Numerical tests show the performance and the robustness of the proposed solution.Index Terms-Nonlinear model predictive control, wheeled unmanned aerial vehicle, nondestructive testing

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A Comparison Between MPC and Optimal PID Controllers: Case Studies

Cited by 35 publications

References 0 publications

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

Residential Community Load Management Based on Optimal Design of Standalone HRES With Model Predictive Control

Multiple Model Predictive Functional Control for Marine Diesel Engine

Nonlinear Model Predictive Control for the Stabilization of a Wheeled Unmanned Aerial Vehicle on a Pipe

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