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

Kähm et al., 2018 - Google Patents

Lyapunov exponents with Model Predictive Control for exothermic batch reactors

Kähm et al., 2018

View PDF
Document ID
4687761265405699221
Author
Kähm W
Vassiliadis V
Publication year
Publication venue
IFAC-PapersOnLine

External Links

Snippet

Thermal runaways cause significant safety issues and financial loss for industrial batch reactors due to the disruption of normal operation. The intensification of processes is restricted, since control systems are not capable of detecting stability boundaries of the …
Continue reading at folk.ntnu.no (PDF) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive 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
    • G05B13/042Adaptive 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04Adaptive 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
    • G05B13/048Adaptive 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265Adaptive 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
    • G05B13/027Adaptive 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00Systems involving the use of models or simulators of said systems
    • G05B17/02Systems involving the use of models or simulators of said systems electric

Similar Documents

Publication Publication Date Title
CN103761450A (en) Dynamic process fault forecasting method based on fuzzy self-adaptive prediction
Kähm et al. Lyapunov exponents with Model Predictive Control for exothermic batch reactors
Kähm et al. Stability criterion for the intensification of batch processes with model predictive control
Kanavalau et al. Robust thermal stability for batch process intensification with model predictive control
Rashid et al. Handling multi‐rate and missing data in variable duration economic model predictive control of batch processes
Heng et al. Energy-oriented modeling and optimization of a heat treating furnace
Ahmadi et al. Multimodel control of nonlinear systems: An improved gap metric and stability margin-based method
Sidikov et al. Fuzzy synergetic control nonlinear dynamic objects
Kähm et al. Optimal Laypunov exponent parameters for stability analysis of batch reactors with Model Predictive Control
Kummer et al. NMPC-based control scheme for a semi-batch reactor under parameter uncertainty
Vladov et al. Control signals of a predictive industrial PID controller
Li et al. Event-based production control for energy efficiency improvement in sustainable multistage manufacturing systems
Kähm et al. Thermal stability criterion of complex reactions for batch processes
Anderson et al. Distributed economic model predictive control of a catalytic reactor: Evaluation of sequential and iterative architectures
Rohman et al. Implementation of model predictive control in tracking dynamic optimal profiles of semi batch autocatalytic esterification reactor
Zhang et al. Multi-Objective Optimization for Gas Distribution in Continuous Annealing Process
Guojun et al. A real-time updated model predictive control strategy for batch processes based on state estimation
Kahm Thermal stability criteria embedded in avanced control systems for batch process intensification
Clerget et al. Dynamic optimization of a system with input-dependant time delays
Kumar et al. Fuzzy Logic Control of Temperature in Nitration Process
Yu et al. Predictive control based on neural networks of the chemical process
Son et al. Model-plant mismatch learning offset-free model predictive control
Hutabarat et al. Detection and quantification of valve stiction based on normality test and Hammerstein system identification
Alanqar et al. Handling plant variation via error-triggered on-line model identification: Application to economic model predictive control
Gowthami et al. Fault detection and diagnosis in continuous stirred tank reactor (CSTR)