1990
DOI: 10.13182/nt90-a34468
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State Feedback Assisted Classical Control: An Incremental Approach to Control Modernization of Existing and Future Nuclear Reactors and Power Plants

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Cited by 124 publications
(38 citation statements)
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“…(1 ) One group delayed neutron model is utilized and the coolant inlet temperature is treated as a constant [2][3][4].The small perturbation linearization methodology is utilized to linearize the nonlinear core model (1). The transfer function and the state equation of the core are separately calculated and expressed by…”
Section: Modeling For Pwr Corementioning
confidence: 99%
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“…(1 ) One group delayed neutron model is utilized and the coolant inlet temperature is treated as a constant [2][3][4].The small perturbation linearization methodology is utilized to linearize the nonlinear core model (1). The transfer function and the state equation of the core are separately calculated and expressed by…”
Section: Modeling For Pwr Corementioning
confidence: 99%
“…Several researchers have made great efforts for the improvement of reactor core power control systems.The state-feedback basedcontrol with classical control part was proposed by Edwards et al [1][2] to devise power control systems of pressurized water reactor (PWR) cores. The linear quadratic Gaussian with loop transfer recovery (LQG/LTR) control wasadopted to contrivePWR core controllers for power regulations [3][4].…”
Section: Introductionmentioning
confidence: 99%
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“…Edwards et al [2,3] proposed the state-feedback assisted classical control (SFAC) for regulating the power of reactor cores which retains a classical output-feedback control part and uses state-feedback to modify reference load signals so that desired reference inputs can be obtained. Simulations showed that SFAC is competent to perform power regulations.…”
Section: Feedback Control With State Observermentioning
confidence: 99%
“…Improving power regulation technology of cores by the introduction of control algorithms is an important measure for safety and availability of NPPs. Over the decades, many control algorithms have been exploited and applied by researchers to core power regulations, which are the stateor output-feedback control with a state observer [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17], the optimal control [18,19], the neural network or fuzzy intelligent control [20][21][22][23][24][25], the model predictive control [26][27][28], the H ∞ robust control [29][30][31], the sliding model control [32][33][34][35], the fractional order control [36][37][38][39][40][41] and other control algorithms [42][43][44][45][46][47]…”
Section: Introductionmentioning
confidence: 99%