Papers by Keyword: Predictive Control

Abstract: This paper deals with a proposal of predictive control system for the magnesite thermal treatment in rotary furnace. The mathematical model based on the initial principles and elementary balances method providing a comprehensive view of the rotary furnace work was calibrated based on the measured operating data. This model was used as the data model for the development of the approximation model in the form of an artificial neural network after identifying the critical points of the production process of sintered magnesia production. The paper represents the process of the approximation model development and the principle of the seeking of the optimal values of the specified control variables in order to ensure the required quality throughout the whole period of the rotary furnace operation.

Abstract: This article is devoted to review of the existing mobile water treatment complex. Development of resource-efficient technology for water purification is examined by the change of process chart as a function of qualitative composition of a water source. Machine design variants are proposed on the terrain vehicle.

Abstract: According to the unsatisfied control result in a military inertial navigation platform,a control method combined with generalized predictive control and PID control is proposed,accurate control can be realized in terms of time and temperature. MATLAB simulation is given to illustrate that this method satisfies expected requirements well,and is feasible and available.

Abstract: Cement decomposing furnace is a typical multi-variable, nonlinear, large delay and strong coupling complex control object, its difficult to establish accurate mathematical model, the conventional control algorithm is difficult to get satisfactory control effect. By applying adaptive BP(back propagation) algorithm in neural network modeling, make the neural network predicts the decomposing furnace outlet temperature, then modify the pulverized coal flow rate value that obtained by the fuzzy controller to control the decomposing furnace outlet temperature. The field application shows that the control software which is designed by the control algorithm in this paper responses quickly, the error between actual temperature and the expected value is small, it has a good reliability, adaptability and robustness.

Abstract: Chain type coal-fired hot blast furnace boiler has a strong coupling, large delay, large inertia characteristics. Control effect of control method of mathematic modeling method and the classical routine of it is very difficult to produce the ideal. The predictive control theory combined with neural network theory. Through the model correction and rolling optimization control method of the system is good to overcome the effects of model error and time-varying process. The experimental results showed that neural network predictive control system is improved effectively the static precision and dynamic characteristic. It has better practicability of boiler temperature of this kind of large time delay system.

Abstract: In this paper, an increment-type multi-step predictive and multi-step control algorithm of single-variable systems based on Laguerre function approximate model is presented, and then the stability of this algorithm is analyzed. Additionally, simulation of this algorithm had been done to investigate performance, the results show that the controlling quality of this algorithm is fairly good.

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.

Abstract: The purpose of this paper is to present a new predictive control utilizing online data and stored data of input/output of the controlled system. The conventional predictive control methods utilize the mathematical model of the control system to predict an optimal future input to control the system. The model is usually obtained by a standard system identification method from the measured input/output data. The proposed method does not require the mathematical model to predict the optimal future control input to achieve the desired output. This control strategy, called just-in-time, was originally proposed by Inoue and Yamamoto in 2004. In this paper, we proposed a simplified version of the original just-in-time predictive control method.

Abstract: Network latency was usually uncertain or random, and the packet loss and temporal disorders could also be attributed to a certain degree of time delay. This paper briefly described the basic principle of predictive control and deduced the predictive control algorithm based on Toeplitz equation, finally combined with the simulation example to verify the validity and superiority of the new algorithm, from the operation speed of the algorithm, the signal tracking capabilities when time delay existed, and performance for overcoming the influence of model mismatch.

Abstract: Remote vehicle steering assist is quite necessary for reducing traffic accidents when the driver is in risky driving states such as fatigue, drunk and so on. Communication such as internet, GPS and GSM is usually applied in this kind of remote control process. During network transmission, data packets were inevitably lost more or less, which has negative influence on the remote steering operation. In order to solve this problem, model of some remote steering system was built so as to analyze the steering quality. A packet dropout compensator was designed and applied from the aspect of predictive compensate control using hybrid pi-sigmoid fuzzy neural network. Simulation results showed that the compensator worked effectively to reduce the bad influence of packet dropout during remote vehicle steering procedure.