Xiaojuan Lu, Qingbo Zhang^*

Energy Engineering, Vol.118, No.6, pp. 1729-1740, 2021, DOI:10.32604/EE.2021.014938

Abstract In the process of grid-connected photovoltaic power generation, there are high requirements for the quality of the power that the inverter breaks into the grid. In this work, to improve the power quality of the grid-connected inverter into the grid, and the output of the system can meet the grid-connected requirements more quickly and accurately, we exhibit an approach toward establishing a mixed logical dynamical (MLD) model where logic variables were introduced to switch dynamics of the single-phase photovoltaic inverters. Besides, based on the model, our recent efforts in studying the finite control set model predictive control (FCS-MPC) and devising… More >

Ibrahim Atawi¹, Sherif Zaid^1,2,3,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 449-469, 2022, DOI:10.32604/iasc.2022.019959

Abstract Transformerless inverters have become an important integration of the modern photovoltaic (PV) grid-tied systems. Unfortunately, it has a general safety problem regarding the earth leakage current that must be less than the recommended standards. Lately, the H7 transformerless inverter, which is a three-phase inverter with an additional switch on the DC side, is introduced to mitigate the earth leakage current. Different modulation techniques and controllers are proposed to optimize its performance. This paper proposed the application of model predictive control (MPC) to grid-connected H7 transformerless inverter supplied by the PV power system. In modeling the system, the grid inductance has… More >

Buddhadeva Sahoo^1,*, Sangram Keshari Routray², Pravat Kumar Rout², Mohammed M. Alhaider³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1851-1875, 2021, DOI:10.32604/cmc.2021.018535

Abstract This paper suggests a combined novel control strategy for DFIG based wind power systems (WPS) under both nonlinear and unbalanced load conditions. The combined control approach is designed by coordinating the machine side converter (MSC) and the load side converter (LSC) control approaches. The proposed MSC control approach is designed by using a model predictive control (MPC) approach to generate appropriate real and reactive power. The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation. It shows its superiority by eliminating the requirement of transformation, switching table, and the PWM… More >

Xiaojuan Lu, Zeping Liang^*

Energy Engineering, Vol.118, No.4, pp. 1171-1183, 2021, DOI:10.32604/EE.2021.014724

Abstract There are two prominent features in the process of temperature control in solar collector field. Firstly, the dynamic model of solar collector field is nonlinear and complex, which needs to be simplified. Secondly, there are a lot of random and uncontrollable, measurable and unmeasurable disturbances in solar collector field. This paper uses Taylor formula and difference approximation method to design a dynamic matrix predictive control (DMC) by linearizing and discretizing the dynamic model of the solar collector field. In addition, the purpose of controlling the stability of the outlet solar field salt temperature is achieved by adjusting the mass flow… More >

Xiaokan Wang^*, Qiong Wang

Journal on Internet of Things, Vol.2, No.2, pp. 81-87, 2020, DOI:10.32604/jiot.2020.010225

Abstract A good hybrid vehicle control strategy cannot only meet the power requirements of the vehicle, but also effectively save fuel and reduce emissions. In this paper, the construction of model predictive control in hybrid electric vehicle is proposed. The solving process and the use of reference trajectory are discussed for the application of MPC based on dynamic programming algorithm. The simulation of hybrid electric vehicle is carried out under a specific working condition. The simulation results show that the control strategy can effectively reduce fuel consumption when the torque of engine and motor is reasonably distributed, and the effectiveness of… More >

Aymen Rhouma^1,∗, Sami Hafsi^2,†, Faouzi Bouani³

Computer Systems Science and Engineering, Vol.34, No.5, pp. 305-313, 2019, DOI:10.32604/csse.2019.34.305

Abstract This paper provides an application of Fractional Model Predictive Control (FMPC) and fractional-order Proportional Integral controller (P I^λ) on a thermal system with time delay.The first controller is based on Grünwald-Letnikov’s method to predict the future dynamic behavior of the system. This method consists in replacing the non-integer derivation operator of the adopted system representation by a discrete approximation. Therefore, this controller is developed on the basis of a fractional order model. However, the second controller is founded on an extended version of Hermite-Biehler theorem to determine the complete set stabilizing P I^λ parameters Experiment results onto a time delay… More >

Dehua Shi^1,4, Shaohua Wang^1,2,*, Yingfeng Cai¹, Long Chen¹, ChaoChun Yuan¹, ChunFang Yin³

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 27-39, 2020, DOI:10.31209/2018.100000062

Abstract Model predictive control (MPC), owing to the capability of dealing with nonlinear and constrained problems, is quite promising for optimization. Different MPC strategies are investigated to optimize HEV nonlinear energy management for better fuel economy. Based on Bellman’s principle, dynamic programming is firstly used in the limited horizon to obtain optimal solutions. By considering MPC as a nonlinear programming problem, sequential quadratic programming (SQP) is used to obtain the descent directions of control variables and the current control input is further derived. To reduce computation and meet the requirements of real-time control, the nonlinear model of the system is approximated… More >

Yueqi Hou¹, Xiaolong Liang^{1, 2}, Lyulong He¹, Jiaqiang Zhang^{1, *}, Jie Zhu³, Baoxiang Ren³

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1335-1349, 2020, DOI:10.32604/cmc.2020.06869

Abstract Consensus control of multi-agent systems has attracted compelling attentions from various scientific communities for its promising applications. This paper presents a discrete-time consensus protocol for a class of multi-agent systems with switching topologies and input constraints based on distributed predictive control scheme. The consensus protocol is not only distributed but also depends on the errors of states between agent and its neighbors. We focus mainly on dealing with the input constraints and a distributed model predictive control scheme is developed to achieve stable consensus under the condition that both velocity and acceleration constraints are included simultaneously. The acceleration constraint is… More >

Kai Liu^{1, 2}, Zheng Hou^{2, *}, Zhiyong She², Jian Guo²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 131-148, 2020, DOI:10.32604/cmes.2020.08124

Abstract This paper studies the reentry attitude tracking control problem for hypersonic vehicles (HSV) equipped with reaction control systems (RCS) and aerodynamic surfaces. The attitude dynamical model of the hypersonic vehicles is established, and the simplified longitudinal and lateral dynamic models are obtained, respectively. Then, the compound control allocation strategy is provided and the model predictive controller is designed for the pitch channel. Furthermore, considering the complicated jet interaction effect of HSV during RCS is working, an improved model predictive control approach is presented by introducing the online parameter estimation of the jet interaction coefficient for dealing with the uncertainty and… More >

A. Parassuram^1,*, P. Somasundaram¹

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.2, pp. 169-187, 2018, DOI:10.31614/cmes.2018.01720

Abstract A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control (LFC). A dynamic model of an interconnected power system was used for Model Predictive Controller (MPC) design. MPC predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain matrix. In this paper, the optimal closed loop feedback gain matrix was calculated using Kautz function. Being an Orthonormal Basis Function (OBF), Kautz function has an advantage of solving complex pole-based nonlinear system. Genetic Algorithm (GA) was applied to optimally tune the Kautz function-based MPC. A… More >