[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Wu et al., 2014 - Google Patents

Design of dynamic matrix control based PID for residual oil outlet temperature in a coke furnace

Wu et al., 2014

View PDF
Document ID
16206712645166593479
Author
Wu S
Zhang R
Lu R
Gao F
Publication year
Publication venue
Chemometrics and Intelligent Laboratory Systems

External Links

Snippet

The application of proportional–integral–derivative (PID) controllers to chemical processes may not achieve the desired effect due to large time delay, model/plant mismatches, etc, which causes performance deterioration. In view of this, the paper first proposes a new PID …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/048—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/32—Automatic controllers electric with inputs from more than one sensing element; with outputs to more than one correcting element
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems

Similar Documents

Publication Publication Date Title
Wu et al. Design of dynamic matrix control based PID for residual oil outlet temperature in a coke furnace
Kumbasar et al. Adaptive fuzzy model based inverse controller design using BB-BC optimization algorithm
Meng et al. Adaptive neural control of high-order uncertain nonaffine systems: A transformation to affine systems approach
Zhang et al. Improved PI controller based on predictive functional control for liquid level regulation in a coke fractionation tower
Pawlowski et al. Improving feedforward disturbance compensation capabilities in generalized predictive control
Zou et al. Design of fractional order predictive functional control for fractional industrial processes
Zhang et al. Multivariable decoupling predictive functional control with non-zero–pole cancellation and state weighting: Application on chamber pressure in a coke furnace
Zhang Design of a new PID controller using predictive functional control optimization for chamber pressure in a coke furnace
Ye et al. Global approximation of self-optimizing controlled variables with average loss minimization
Shi et al. A design method for indirect iterative learning control based on two-dimensional generalized predictive control algorithm
Martins et al. Robust model predictive control of integrating time delay processes
Bagheri et al. An analytical tuning approach to multivariable model predictive controllers
Khalilipour et al. Nonsquare multivariable non-minimal state space-proportional integral plus (NMSS-PIP) control for atmospheric crude oil distillation column
Ławryńczuk Explicit nonlinear predictive control algorithms with neural approximation
Sun et al. Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions
Wu Multivariable PID control using improved state space model predictive control optimization
Li et al. Optimal disturbance rejection control approach based on a compound neural network prediction method
Su et al. Online reinforcement learning for a class of partially unknown continuous‐time nonlinear systems via value iteration
Pataro et al. A stabilizing predictive controller with implicit feedforward compensation for stable and time-delayed systems
Pasamontes et al. A switching control strategy applied to a solar collector field
Ren et al. Proportion integral-type active disturbance rejection generalized predictive control for distillation process based on grey wolf optimization parameter tuning
Tao et al. PFC based PID design using genetic algorithm for chamber pressure in a coke furnace
Zhao et al. Local self-optimizing control based on extremum seeking control
Zhang et al. An improved decoupling structure based state space MPC design with improved performance
Konakom et al. Batch control improvement by model predictive control based on multiple reduced-models