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 >

Yonghua Zhou¹, Xun Yang¹, Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.92, No.5, pp. 477-491, 2013, DOI:10.3970/cmes.2013.092.477

Abstract Route selections for vehicles can be equivalent to determine the optimized operation processes for vehicles which intertwine with each other. This paper attempts to utilize the whole methodology of model predictive control to engender rational routes for vehicles, which involves three important parts, i.e. simulation prediction, rolling optimization and feedback adjustment. The route decisions are implemented over the rolling prediction horizon taking the real-time feedback information and the future intertwined operation processes into account. The driving behaviors and route selection speculations of drivers and even traffic propagation models are on-line identified and adapted for the simulation prediction in next prediction… More >

Yonghua Zhou¹ , Xun Yang¹ , Chao Mi¹

CMES-Computer Modeling in Engineering & Sciences, Vol.90, No.6, pp. 415-437, 2013, DOI:10.3970/cmes.2013.090.415

Abstract High-speed train transportation is organized in a way of globally centralized planning and locally autonomous adjustment with the real-time known positions, speeds and other state information of trains. The hierarchical integration architecture composed of top, middle and bottom levels is proposed based on model predictive control (MPC) for the real-time scheduling and control. The middle-level trajectory configuration and tractive force setpoints play a critical role in fulfilling the top-level scheduling commands and guaranteeing the controllability of bottomlevel train operations. In the middle-level MPC-based train operation planning, the continuous cellular automaton model of train movements is proposed to dynamically configure the… More >