Enhanced decentralized PI control for fluidized bed combustor via advanced disturbance observer

Sun, Li; Li, Donghai; Lee, Kwang Y.

doi:10.1016/j.conengprac.2015.05.014

Cited by 79 publications

(45 citation statements)

References 24 publications

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“…However, the control performance may deteriorate greatly if the process characteristics vary significantly with the operating conditions. To examine the nonlinearity of the SOFC plant, a common method is to compare the characteristics of the linearized models at different operating conditions [25,26]. Around the nominal operation point with q f = 0.7023 mol/s, I = 300 A, V dc = 333 V, the nonlinear model (1) can be linearized as a transfer function model,…”

Section: Control Difficultiesmentioning

confidence: 99%

A Combined Voltage Control Strategy for Fuel Cell

et al. 2017

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Control of output voltage is critical for the power quality of solid oxide fuel cells (SOFCs), which is, however, challenging due to electrochemical nonlinearity, load disturbances, modelling uncertainties, and actuator constraints. Moreover, the fuel utilization rate should be limited within a safety range during the voltage regulation transient. The current research is usually appealing to model predictive control (MPC) by formulating the difficulties into a constrained optimization problem, but its huge computational complexity makes it formidable for real-time implementation in practice. To this end, this paper aims to develop a combined control structure, with basic function blocks, to fulfill the objectives with minor computation. Firstly, the disturbance, nonlinearity and uncertainties are lumped as a total disturbance, which is estimated and mitigated by active disturbance rejection controller (ADRC). Secondly, a feed-forward controller is introduced to improve the load disturbance rejection response. Finally, the constraints are satisfied by designing a cautious switching strategy. The simulation results show that the nominal performance of the proposed strategy is comparable to MPC. In the presence of parameter perturbation, the proposed strategy shows a better performance than MPC.Sustainability 2017, 9, 1517 2 of 15 the fuel utilization. Based on the benchmark model proposed in [3], it was revealed in [4,5] that the proportional-integral (PI) controller and even the H ∞ optimal control are not able to give a satisfactory performance without exceeding the safety range of the fuel utilization.To this end, the mainstream research resorts to Model Predictive Control (MPC), which is particularly suitable for constrained optimization. A data-driven linear MPC strategy was introduced in [6] based on the subspace identification. To further accommodate the nonlinearities, many nonlinear MPC (NMPC) strategyies [7-10] were developed based on much more complex heuristic models. The simulation results prove the capability of the above MPC methods under the nominal condition. However, the huge online computational requirement limits its wide application. Moreover, the implementation of MPC relies on a high-performance computer which needs to synchronously communicate with the existing Distributed Control System (DCS) through certain ports and protocols [11]. Additional hardware complexity will bring more security risks, which is not favored by the field engineers. Besides the complexity, another drawback of MPC is that the performance may deteriorate greatly in the presence of modelling uncertainties.The industrial engineers argued in [12] that use of MPC is only suitable for the applications where the process size, complexity and potential economic benefits justify the expenditure and technical support requirements. In other words, it is not necessary to adopt MPC in the cases where the control objectives can also be fulfilled by the configuration of the regular function blocks, such as simple algebraic and logic ...

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Section: Control Difficultiesmentioning

confidence: 99%

A Combined Voltage Control Strategy for Fuel Cell

et al. 2017

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“…With the modified EID-based control method proposed in this paper, the performance is enhanced significantly, where the steady-state error drops to 16.87°C (peak-to-peak), as shown in Fig. 14. For comparison, we also design a DOB [27] control system, where K P , K R , and L are the same as (48) and (49). The simulation result is shown in Figs.…”

Section: Simulationmentioning

confidence: 99%

EID‐Estimation‐Based Periodic Disturbance Rejection for Sintering Ignition Process with Input Time Delay

Chen

Wei

et al. 2017

Asian Journal of Control

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Sintering plays a key role in generating blast furnace burden in metallurgical processes. The continuous production and stable quality of sintering significantly depends on the stable and precise control of sintering ignition, which, however, is achieved through an input time delay system, and suffers from different and unknown disturbances. To reject disturbances and enhance the control precision of ignition temperature, this paper introduces a modified equivalent input disturbance (EID)-based disturbance compensation that is suitable for controlling sintering ignition. First, the periodic properties of disturbances induced by gas pressure fluctuations are obtained based on spectral density decomposition. Second, to obtain the dynamics of sintering ignition, an iterative subspace modeling method is developed, which estimates not only the model parameters but also the length of time delay. By considering the periodic property, a control structure of sintering ignition based on the modified EID-based compensation is proposed, in which an additional time-delay element is designed to make the phase difference between EID estimation and real disturbance close to zero. Finally, the validity of the proposed method is verified by a simulation.

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“…[27] with respect to time and substituting Eqs [21], [34] and (A.4) into it lead to [27] with respect to time and substituting Eqs [21], [34] and (A.4) into it lead to …”

Section: Appendix Amentioning

confidence: 99%

“…Differentiating Eq. [27] with respect to time and substituting Eqs [21], [34] and (A.4) into it lead to…”

Section: Appendix Amentioning

confidence: 99%

“…In [27], an advanced disturbance observer is proposed to accommodate time delay and non-minimum phase characteristics and enhanced decentralized Proportional Integral (PI) control is designed for fluidized bed combustor via the observer. In order to eliminate the adverse effects caused by the unknown external disturbance, the disturbance observer is applied as a feedforward compensator in a variety of mechanisms.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Boundary and Distributed Control for a Nonlinear Three‐Dimensional Euler‐Bernoulli Beam Based On Infinite Dimensional Disturbance Observer

Jiang

Liu

2016

Asian Journal of Control

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Control problems in spatially distributed systems are challenging because the disturbance is of infinite dimensions. To this end, this paper discusses an infinite dimensional disturbance observer design, which is illustrated based on a partial differential equation (PDE) model of a nonlinear three-dimensional Euler-Bernoulli beam. The basic idea of the observer design is to modify the estimations based on the difference between the estimated output and actual output. Moreover, an auxiliary parameter system is established to help with the analysis. Then a Lyapunov function candidate consisting of the energy of the system, the observer error and an auxiliary term is given. After a series of analyses of the function, distributed controllers and boundary controllers based on the proposed observer are given to restrain vibration. Finally, by numerical simulations, the convergence of the observer is demonstrated, and the efficacy of control performance is also shown.

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Enhanced decentralized PI control for fluidized bed combustor via advanced disturbance observer

Cited by 79 publications

References 24 publications

A Combined Voltage Control Strategy for Fuel Cell

A Combined Voltage Control Strategy for Fuel Cell

EID‐Estimation‐Based Periodic Disturbance Rejection for Sintering Ignition Process with Input Time Delay

Boundary and Distributed Control for a Nonlinear Three‐Dimensional Euler‐Bernoulli Beam Based On Infinite Dimensional Disturbance Observer

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