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In this paper, the problem of model predictive control for drum water level of boiler systems is investigated. The parameter uncertainties are time-varying norm-bounded and the non-linearity is assumed to satisfy the boundedness condition. The aim is to design a state-feedback controller which minimizes an upper bound on a quadratic objective function at each sampling instant. The hard constraint...
A novel image based visual servoing (IBVS) method under the predictive control frame is proposed in order to solve the visual tracking problem of robot manipulator with multiple constraints. A vision predictive frame is presented by employing the motion model between camera's velocity and image features. And the design step of vision predictive controller is presented. Then, an effective vision predictive...
As a feedforward control strategy, iterative learning control (ILC) is used to track a pre-defined reference and reject repetitive disturbances iteratively, but it is incapable of compensating for non-repetitive disturbances. Thus, ILC is often combined with a well-designed feedback controller. Considering nonlinear process, this paper presents an integrated ILC and on-line model predictive (MPC)...
This study proposes a high precision selective harmonic compensation scheme for active power filters, which designed by using the basic theory of GPC. A generalized predictive control (GPC) strategy based on the transfer function model is adopted. The GPC can compensate the delay in detecting the harmonic and the better result of compensation for harmonic can be achieved. As Kalman filter can detect...
The generalized predictive control is applied to the industrial arc furnace electrode regulator system. The detailed design procedure of the generalized predictive controller is presented. Based on multi-step prediction, rolling optimization and online correction, the optimal control law is obtained. The results of simulation show that this proposed algorithm can restrain arc disturbance effectively,...
The online computational burden associated with the solution of the NMPC optimization problem is a key issue when applying nonlinear model predictive control (MPC) to fast dynamic systems. In order to improve the computation efficiency, a novel hardware implementation method for NMPC on a field programmable gate array (FPGA) chip is proposed. The optimization problem formed by NMPC is solved by particle...
A T-S fuzzy model is used as predictive model to get estimated value of output, and corrects the estimated output value by using the available process variable. Then in terms of optimal control theory, the control law, which is used to control the whole system, is calculated by the corrected estimated value and set-point. State estimator is introduced into state feedback predictive control based on...
Point to nonlinear time varying and a long time delay of electric heating oil furnace, fuzzy predictive control is designed to solve the temperature of electric heating oil furnace, which chooses C8051F020 single chip computer as the core of control system and implements the fuzzy predictive control. The result proves this system has sensitive control high stability, stable running and effective saving...
The traditional control methods are not able to keep control performance in a high level because response speed becomes more important for industrial control. This paper presented a fast predictive control algorithm, which was easy and simple to calculate and the principle of algorithm was very clear and greatly improved the speed of response and calculation, as well as demonstrated the principles...
The main contribution of this paper is the development of hybrid model predictive control and fault detection strategy for wind energy conversion system (WECS) based on mixed logic dynamic (MLD) model framework. The MLD model for WECS including multiple work regions is established. Also the hybrid model predictive control method based on the MLD model of WECS is adopted to implement the variable speed...
Least square support vector machine is a kind of thought to solve structural risk minimization method, weighted least squares support vector machine is introduced to solve the exist robustness, sparsity and large-scale computational problems, since the weighted method easily leads to shortcomings of over-fitting, according to the Cauchy distribution characteristics, weighted least squares support...
After analyzing the NCS application advantages and Disadvantages of Ethernet and TCP/IP network, the model predictive control algorithm is used to explore the transmission delay of the network control system. A delay compensation control scheme which based on dynamic matrix control algorithm is given. The scheme is proved to be effective by simulation.
In this study, a neural network (NN) based dynamic Mach number predictive control was proposed for a wind tunnel Match number control system. The proposed method absorbed in advantages both artificial neural network and model predictive control, for control of strong nonlinear, multiple variables, large lagging, and time-varying system. In this approach, the dynamic of wind tunnel is represented by...
Supervisory predictive control based on GPC theory is an effective control algorithm for complex industrial process which can be realized by adding a supervisory optimal level without modifying the regulatory level. In this paper supervisory predictive control is studied and applied in drum-type boiler-turbine system which is characterized by nonlinearity. Therefore, T-S fuzzy model is used to approximate...
The stability analysis problem is investigated for networked predictive control systems with varying controller gains in this paper. By introducing a new auxiliary variable and analyzing the deep relationship between two consecutive sampling points, the NCS is transformed into a coupled switched system. The sufficient condition guaranteeing the asymptotical stability of the coupled switched system...
In order to solve the problem that model predictive control, MPC, is difficult to apply to the large scale system or fast dynamic system, in this paper, we describe a new fast online optimization predictive control method. This method is to exploit the structure of the QPs that arise in MPC, reorder the appropriate variable and use the advanced interior-point to improve the control performance and...
Contouring control can provide precision machine tool control an effective method, and many methods have been proposed to date. Direct drive of linear motor is the inevitable demand and trends for improving CNC processing speed and precision. XY table contouring systems involve competing control objective of maximizing accuracy while minimizing traversal time. To meet high-speed, high precision and...
Fuzzy supervisory predictive control based on genetic algorithm optimization is proposed. For the nonlinear model, through a general objective function dynamically optimized to determine the optimal set-point for a given regulatory level, by using genetic algorithm in order to solve the nonlinear optimization problem for the setpoint, and compared with the supervisory predictive control based on linear...
In this paper a current predictive control strategy for grid side converter was proposed, which is of fixed switching frequency, the sinusoidal output current, and fast dynamic response. Experimental platform based on Infineon XC2785X was built. Experimental results showed that the control strategy is feasible and efficient.
A fast-rate model is obtained by transforming a system with state time-delay into a system without time-delay. Based on the fast-rate model, a dual-rate inferential predictive controller is designed and a new method on designing dual-rate inferential predictive controller for systems with state time-delay is given. Finally, a numerical example is given to illustrate the effectiveness of the proposed...
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