Papers by Keyword: Predictive Control

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Authors: Ling Li, Ye Guo Sun
Abstract: In this paper, the predictive control of a class of networked control systems (NCSs) with time delay is investigated. Under the assumptions of forward completeness of the open-loop system and the existence of a stabilizing controller, state feedback and output feedback controllers are designed which achieves global asymptotic stability. Lastly, an illustrative example is given to demonstrate the effectiveness of the proposed results.
Authors: Gang Wu, Zhe Jing Bao, Ting Wu, Wen Jun Yan
Abstract: In this paper the predictive control of switching system is introduced to the DC/AC converter. Our aim is to control the output power of converter closer to the reference. By considering the working status of DC/AC converter is actually switched among several definite subsystems, the switching system model of DC/AC converter is constructed. The tracking problem of converter output power can be changed to be that of its three-phase output currents. Based on the switching system model of converter, the three-phase output currents of those subsystems are predicted and the switching command is determined by examining the discrepancies between the three-phase predictive currents corresponding to each subsystem and the reference ones. Simulations demonstrate that our control scheme for DC/AC converter connected with ultra-capacitor has great advantages in output power tracking and sinusoidal output current waveforms.
Authors: Jie Jia Li, Ben Wang, Xiao Yan Guo, Lu Lu Sun
Abstract: An air supply control method of VAV system based on BP neural network is proposed in this paper, which combines with the recurrent wavelet neural network model, predictive control and optimization of parameters. With the proposed method, the air volume of the VAV system can be controlled accurately even if the change of the air is nonlinear and time-lapse. Compared with tradition control method, it has the advantages of rapidly converging, high control precision, strong skills of learning and wide application prospect.
Authors: Zhen Xing Gao, Zheng Qiang Li
Abstract: Low altitude wind shear badly threatens aircrafts’ flight safety. Since flight states change rapidly during flying through wind shear, it is deficient to design an optimization controller by off-line analyse. A ring-vortex microburst wind shear model and B747 aircraft flight dynamics model were built. For glide slope tracking under wind shear, an off-line controller was designed by linear quadratic method. Furthermore, a model predictive controller with sequential optimization was designed. Simulation results show the on-line sequential optimization controller possess better tracking performance.
Authors: Shi He Chen, Xi Zhang, Wei Wu Yan, Guo Liang Wang
Abstract: In this paper, targeted at reheated steam temperatures large time delay and strong nonlinearity characteristics in power plant, a multi-model predictive control strategy is proposed in light of the nonlinear characteristics of steam temperature control. This strategy utilizes the linearized model of nonlinear process at multiple working points to divide the process into several subspaces. A relatively accurate fixed model can be found in each subspace. Based on this, a global approximation model of complex object could be obtained. Simulation and application results show no matter for stable or load varying process, reheated steam temperature can be maintained in the required control range. It is much superior to the traditional PID control method.
Authors: Zai Ping Chen, Xue Wang
Abstract: According to the random time-delay exist in sensor-controller channel and controller-actuator channel in networked control systems, an adaptive predictive control strategy was proposed. In this control strategy, an improved generalized predictive control algorithm is adopted to compensate the networked random time-delay. In addition, using the recursive least squares with a variable forgetting factor algorithm to indentify the model parameters of controlled object on-line, through the way, it could adjust the systems with unknown parameters adaptively. Simulation results show that the adaptive predictive control proposed could solve random time-delay of networked control systems effectively.
Authors: Zhong Tao Liu, Zheng Hua Feng
Abstract: Two-dimensional landslide model system is an important experimental platform for studying geological disaster, landslide behavior in different conditions are achieved by controlling the hydraulic pump drive model platform uplifting cabinet inclination. During the process of automation transformation of the two-dimensional landslide model system, control system based on computer is used to achieve a smooth lifting and precise angle of landslide model platform. Thanks to predictive control algorithm of least squares support vector machine (LS-SVM) model used in this paper, random real-time change of equivalent load applied on the hydraulic cylinder system effectively solved. The control system of the two-dimensional landslide model effectively eliminated crawling effect and pulse lifting in the condition of low speed and high load conditions of hydraulic system.
Authors: Bin He, Da Peng Jiang, Guo Cheng Zhang, Ying Hao Zhang
Abstract: S surface control is a simple and operative motion control algorithm for underwater vehicles, but it has two parameters requiring to be adjusted manually. In order to enhance the adaptability of S surface controller, the research of S surface controller parameter self-tuning methods based on rules and models is carried out. Firstly, combined with fuzzy control, parameter self-tuning method based on fuzzy rules is presented. Then by means of predictive control theory, model-based parameter self-tuning method is proposed. By introducing the nonlinear autoregressive moving average model, the prediction model of underwater vehicles is established using parallel Elman neural network, and the optimal parameters of S surface controller is obtained by constructing quadratic performance index function. The results of simulation experiments show that the response speed of S surface controller with parameter self-tuning modules is improved, and the parameter self-tuning methods is demonstrated feasible and effective.
Authors: Yan Ping Feng, Da Chang Zhu
Abstract: Many projects have the characteristic of large-scale, wide-rang, and at very important role in national economy. Nowadays engineering project management is still suffering from many problems due to various uncertainties kind of risks. Risk management is a crucial parts of successful engineering project management, but it is often not well predictive in many projects. Risk predictive is valuable and essential for decision support system. But risk factors in projects are complex and couple with each other, and normal risk predictive can not manifest this relationship fully. According to the uncertainness parameters in risk management, predictive control strategy is proposed in this paper. Considering the nonlinear dynamical process, the model of external disturbance is built as a part of control system, and its stability is also analyzed. The effectiveness of the proposed method is demonstrated through a numerical simulation.
Authors: Lu Jun Wang, Tao Gong, Jun Zhu
Abstract: In this paper, the state space model of neutral point clamped three-level grid-connected inverter is detailed derived and an Robust Predictive Control (RPC) method is proposed. In the proposed method, the total 27 switching vectors composed of a finite set from which the optimal switching vector is selected according to a cost function. The robust performance is improved just by increasing switching frequency. Experimental results show that the proposed method has a flexible control purposes and we can optimize the synthesize performance just by adjusting weighting coefficients of cost function. In addition, RPC controller has a robust performance in tracking output reference current and balancing neutral point voltage.
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