Design of Fast Output Sampling Controller for Three-Time-Scale Systems: Application to Spatial Control of Advanced Heavy Water Reactor

Shimjith, S. R.; Tiwari, A.P.; Bandyopadhyay, B.

doi:10.1109/tns.2011.2170850

Cited by 31 publications

(24 citation statements)

References 17 publications

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“…, (δξ 17 /ξ 17 0 )] T , ξ = X, I , C, x, P, in which δ denotes the deviation from the respective steady-state value of the variable. Likewise, define the input vector as u = [δv 2 δv 4 δv 6 δv 8 ] T (9) with v k as the voltage signal to kth RR drive and output vector as…”

Section: Brief Overview Of Ahwrmentioning

confidence: 99%

“…Note that, the AHWR system has five inputs, namely, four voltage signals to RR drives, mentioned in (9), and a feed water flow rate q f . Feed water flow rate is assumed to be directly proportional to the global reactor power as…”

Section: Brief Overview Of Ahwrmentioning

confidence: 99%

“…This spatial stabilization and control is achieved by proper movement of RRs. Therefore, out of the five inputs, four inputs to RRs [given by (9)] and a feed water flow rate are written separately in (11).…”

Section: Brief Overview Of Ahwrmentioning

confidence: 99%

“…However, these control strategies require a state observer of large order. To overcome this, MROF-based fast output sampling (FOS) control technique is investigated in [9]. In FOS, control signal is generated as a linear combination of a number of output samples collected in one sampling interval, where input sampling time is larger compared with output.…”

Section: Brief Overview Of Ahwrmentioning

confidence: 99%

“…In FOS, control signal is generated as a linear combination of a number of output samples collected in one sampling interval, where input sampling time is larger compared with output. For example, in [9], sampling time for spatial control component of input is taken as 60 s. A similar kind of approach for two-time-scale system is suggested in [25] for AHWR, where the sampling time is taken as 54 s. However, for practical reactor control to work with larger sampling time is not desirable, because in small time, reactor system can undergo a considerable change. Hence, periodic output feedback (POF)-based controller for three-time-scale system of AHWR is presented in [26] with a sampling period of 2 s. Although MROF-based controllers (i.e., FOS and POF) give a very simple control structure, they lack robustness and may not work satisfactorily in the presence of disturbance, parameter variations, and perturbation in operating conditions.…”

Section: Brief Overview Of Ahwrmentioning

confidence: 99%

See 4 more Smart Citations

Discrete-Time Sliding Mode Spatial Control of Advanced Heavy Water Reactor

Munje¹,

Patre²,

Tiwari

2016

IEEE Trans. Contr. Syst. Technol.

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This brief presents the design of a discrete-time sliding mode control (DSMC) for spatial power stabilization of advanced heavy water reactor (AHWR). Mathematical model of AHWR is represented by 90 first-order nonlinear differential equations with 18 outputs and five inputs. The linear model is obtained by linearizing nonlinear equations over the rated power. This linear model is found to be highly ill conditioned and is possessing three-time-scale property. Initially, the linear model is transformed into block diagonal form to separate slow, fast 1, and fast 2 subsystems and then DSMC is designed using slow subsystem alone since fast 1 and fast 2 subsystems are stable. The proposed DSMC strategy is designed using the constant plus proportional rate reaching law with matched disturbance. Finally, the nonlinear multivariable model of AHWR is simulated with the designed controller and the results are generated under different transients. The efficacy of the proposed DSMC is demonstrated with the comparison of prevalent controllers in the literature and the performance is evaluated under the same transient levels.Index Terms-Advanced heavy water reactor (AHWR), composite control, discrete-time sliding mode control (DSMC), global power control in large reactors, reaching law, spatial control.

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Section: Brief Overview Of Ahwrmentioning

confidence: 99%

Section: Brief Overview Of Ahwrmentioning

confidence: 99%