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 >

Chen Shen^1,*, Youping Chen¹, Bing Chen¹, Jingming Xie¹

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 379-397, 2019, DOI:10.32604/cmc.2019.04883

Abstract Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed. As such, the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system. This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations. The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties. Thus, the controller can reduce the need for manual adjustments. The controller… More >