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  • Open Access

    ARTICLE

    Consensus of Multi-Agent Systems with Input Constraints Based on Distributed Predictive Control Scheme

    Yueqi Hou1, Xiaolong Liang1, 2, Lyulong He1, Jiaqiang Zhang1, *, 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 More >

  • Open Access

    ARTICLE

    Reentry Attitude Tracking Control for Hypersonic Vehicle with Reaction Control Systems via Improved Model Predictive Control Approach

    Kai Liu1, 2, Zheng Hou2, *, 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 More >

  • Open Access

    ARTICLE

    Practical Application of Fractional Order Controllers to a Delay Thermal System

    Aymen Rhouma1,∗, Sami Hafsi2,†, 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 Iλ) 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 Iλ parameters Experiment results onto More >

  • Open Access

    ARTICLE

    A Compensation Controller Based on a Nonlinear Wavelet Neural Network for Continuous Material Processing Operations

    Chen Shen1,*, 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… More >

  • Open Access

    ARTICLE

    Kautz Function Based Continuous-Time Model Predictive Controller for Load Frequency Control in a Multi-Area Power System

    A. Parassuram1,*, 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 More >

  • Open Access

    ARTICLE

    Dynamic Route Guidance Based on Model Predictive Control

    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… More >

  • Open Access

    ARTICLE

    Model Predictive Control for High-speed Train with Automatic Trajectory Configuration and Tractive Force Optimization

    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… More >

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