Boiler-turbine Unit Research Articles

Formula omitted] adaptive control for improving load-following capability of nonlinear boiler–turbine units in the presence of unknown uncertainties

Uncertain operating conditions, along with the load demand for a wider and faster response, bring new challenges to the nonlinear boiler–turbine unit control. In order to achieve safe and efficient operations, this paper proposes a novel L1 adaptive state feedback controller for the multivariable nonlinear boiler–turbine systems with unknown uncertainties. This L1 adaptive control approach can achieve arbitrarily close tracking of the reference signal while ensuring closed-loop stability in the presence of strong nonlinearities, internal un-modeled dynamics, time-varying unknown parameters and uncertain dead time within its time-delay margins. In this study, a boiler–turbine unit simulation model is first built in order to verify the algorithm; then the L1 adaptive control approach is presented followed by its main results and proof; only based on one group of the equilibrium working point data, the L1 adaptive controller is designed for the overall working range of the boiler–turbine unit. For a more reliable evaluation on the L1 adaptive controller, the offset-free input-to-state stable fuzzy model predictive controller (OFISS-MPC) – which has all-sided performances – is briefly introduced and functions as a reference for our results. Finally, the L1 adaptive controller is tested in a series of challenging simulation scenarios and then compared with the OFISS-MPC controller. The results validate the expected performances of the L1 adaptive controller for the boiler–turbine unit with unknown uncertainties.

Multivariable robust adaptive sliding mode control of an industrial boiler–turbine in the presence of modeling imprecisions and external disturbances: A comparison with type-I servo controller

To guarantee the safety and efficient performance of the power plant, a robust controller for the boiler–turbine unit is needed. In this paper, a robust adaptive sliding mode controller (RASMC) is proposed to control a nonlinear multi-input multi-output (MIMO) model of industrial boiler–turbine unit, in the presence of unknown bounded uncertainties and external disturbances. To overcome the coupled nonlinearities and investigate the zero dynamics, input–output linearization is performed, and then the new decoupled inputs are derived. To tackle the uncertainties and external disturbances, appropriate adaption laws are introduced. For constructing the RASMC, suitable sliding surface is considered. To guarantee the sliding motion occurrence, appropriate control laws are constructed. Then the robustness and stability of the proposed RASMC is proved via Lyapunov stability theory. To compare the performance of the purposed RASMC with traditional control schemes, a type-I servo controller is designed. To evaluate the performance of the proposed control schemes, simulation studies on nonlinear MIMO dynamic system in the presence of high frequency bounded uncertainties and external disturbances are conducted and compared. Comparison of the results reveals the superiority of proposed RASMC over the traditional control schemes. RAMSC acts efficiently in disturbance rejection and keeping the system behavior in desirable tracking objectives, without the existence of unstable quasi-periodic solutions.

Gain tuning PI controllers for boiler turbine unit using a new hybrid jump PSO

In this paper, a new hybrid jump PSO (HJPSO) is proposed for tuning the gains of PI controllers to the boiler turbine unit. HJPSO based Gaussian and Cauchy mutation is proposed to improve the standard PSO performance. The new strategy is based on observing the local and global best particles which are not improved in a predefined number of iterations and moving these particles to a new best position. Besides, forming a new particle that handles the minimum error of each controller to replace the global best particle if it has best fitness. The simulation results show that the proposed algorithm has its ability in optimizing the control parameters and effectively achieved better performance when compared with other PSO algorithms.

Design and Implementation of a Multiple-Model based Control scheme for Boiler-Turbine Unit

In this work, the authors have proposed a multiple-linear model based control scheme for the boiler-turbine unit. The proposed control scheme makes use of local linear state space models determined at different load conditions, by linearizing the nonlinear boiler-turbine model reported by Bell and Astrom, 1987. Each local linear state space model is stabilized via state feedback approach and is used to design a multiple-linear model based controller for the boiler-turbine unit. Genetic Algorithm is employed to optimally tune the parameters of each local linear controller. The global controller output is determined as a linear combination of all local controller outputs. The extensive simulation studies show that the proposed control scheme effectively handles the input constraints of the boiler-turbine unit and meets the required electrical demand.

Hierarchical optimization of boiler–turbine unit using fuzzy stable model predictive control

This paper develops a hierarchical control system structure based on the Takagi–Sugeno fuzzy model to achieve an optimal control of a boiler–turbine unit. In the upper layer of the hierarchy, an optimal reference governor is designed to find the optimal operating point. A disturbance term is introduced to the fuzzy model to lump the modeling mismatch and unknown disturbance. Thus, the effect of plant behavior variation can be removed and the operating point found can be feasible to control. In the lower layer, a stable model predictive controller is developed to track the optimal set-points while guaranteeing the input-to-state stability of the system. Fuzzy Lyapunov function and appropriate slack and collection matrices are used to reduce the conservatism of stability design and improve the performance. Through the estimation of the disturbance term using an observer, the two layers in the hierarchy are coupled and the integrated system can realize a dynamic optimal control of the boiler–turbine unit, even in the case of severe plant behavior variations.

Predictive control with adaptive model maintenance: Application to power plants

This paper describes a method for model predictive control (MPC) with model maintenance. A supervisor maintains the control model in real time by providing an estimate of disturbances and noise. A switch is triggered when the predictions of the control model deviate from disturbance estimate by more than a pre-determined amount. The predictive control algorithm described in the paper uses the innovation representation of a Markov–Laguerre model. A Monte Carlo study and an experiment show that good models and stable control are obtained. A simulation study based on models of a boiler–turbine unit shows that the algorithm can adapt to time-varying data. The performance is assessed using the area regulation (AR) test criterion currently adopted by PJM Interconnection LLC. The proposed adaptive MPC gives an AR test score of more than 90 with pressure fluctuations less than 3% even when the coal quality changes.

Data-driven modeling and predictive control for boiler–turbine unit using fuzzy clustering and subspace methods

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler–turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler–turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler–turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach.

Suppression of harmonic perturbations and bifurcation control in tracking objectives of a boiler–turbine unit in power grid

In the presence of harmonic disturbances, boiler–turbine units may demonstrate quasi-periodic behaviour due to the occurrence of various types of bifurcation. In this article, a nonlinear model of boiler–turbine unit is considered in which drum pressure, electric output and drum water level are controlled via manipulation of valve positions for fuel, steam and feed-water flow rates. For bifurcation control in tracking problem, two controllers are designed based on gain scheduling and feedback linearization (FBL). To investigate the efficiency of control strategies, three cases are considered for desired tracking objectives (a sequence of steps, ramps/steps, and a combination of them). According to the results, FBL controller works successfully in suppression of harmonic perturbations and consequently bifurcation control. As it is implemented, quasi-periodic solutions (caused by Hopf bifurcation) are vanished; leading to the appearance of periodic solutions with low amplitudes. Consequently, appropriate tracking performance with less oscillatory behaviour is observed for the drum pressure, electric output, and drum water level (desirable for the power grid). In addition, when FBL controller is used, less control efforts are predicted for the bifurcation control.

Derivative-free Estimator Based Non-Linear Model Predictive Control of a Boiler-Turbine Unit

In this work, the authors have proposed a constrained nonlinear model predictive control (NMPC) scheme for a boiler-turbine system. The proposed control scheme relies on the non-linear state space model proposed by Bell and Astrom, 1987 for prediction. A derivative-free Kalman filter has been designed to estimate the state variables of the boiler-turbine unit. These estimated values have been used as an initial condition for predicting the future states and outputs in the NMPC formulation. In order to account for model-plant mismatch and to achieve offset-free control, innovation based correction of predicted states and outputs as suggested by Ricker, 1990 has been incorporated in the proposed NMPC formulation. The extensive simulation studies show that the proposed control scheme effectively handles the input constraints of the boiler-turbine unit and meets the required electrical demand without requiring careful selection of operating points.

Data-Driven Modeling and Predictive Control for Boiler–Turbine Unit

This paper develops a novel data-driven modeling strategy and predictive controller for boiler-turbine unit using subspace identification and multimodel method. To deal with the nonlinear behavior of boiler-turbine unit, the system is divided into a number of local regions following the analysis of the nonlinearity distribution along the operation range, and then the corresponding measurement data are organized to identify the local models through the subspace method. By transforming local models into the same basis, the resulting multimodel system (MMS) is shown to represent the boiler-turbine unit very closely, and thus, used in designing a multimodel-based model predictive control (MMPC). As an alternative approach, a data-driven direct predictive controller (DDPC) is developed by utilizing the intermediate subspace matrices as local predictors. Online update of the predictor is also implemented on the multimodel structure to make the controller responsive to plant behavior variations. Simulation results demonstrate the feasibility and effectiveness of the proposed approach.

Analysis and Control of Once-Through Boiler-Turbine Unit

A nonlinear once-through coal-fired boiler-turbine unit model is introduced and analyzed for the purpose of control system design. Firstly, input-output variable pairing configurations for this 3×3 system are obtained based on static relative gain array and row-Gershgorin band analysis using its linearization model at 100% load. A decentralized PI control system is then deployed and tuned to explore its control system performance as the basis of further study. Results show that the decentralized control structure has good setpoint tracking performance, while the disturbances between loops are still notable due to non-diagonal dominance, thus control strategy of decoupling or disturbance rejection is necessary.

Research on Coordinated Control System for Boiler-Turbine Units Based on Fractional-Order Control

It is important for conventional thermal power units to participate in frequency adjustment and peak regulation for the safe operation of grid side. This paper research on coordinated control system (CCS) for boiler-turbine units based on fractional-order control (FOC). The realization of fractional-order PID (FOPID) controller in distributed control system (DCS) is provided. The engineering application results show that this algorithm is easy to be realized in project by applying all sorts of existing algorithms in DCS. Furthermore, this algorithm can overcome the large lag and inertia for boiler and improve the primary frequency and automatic generation control (AGC) tracking performance in boiler-turbine CCS effectively.

Nonlinear dynamics and control of bifurcation to regulate the performance of a boiler–turbine unit

The economical operations of power plants and environmental awareness are the major factors affecting the importance of control in boiler–turbine units. In this paper, a multivariable nonlinear model of boiler–turbine unit is considered. Drum pressure, electric output and water level of drum (as output variables) are adjusted at desired values by manipulation of valve positions for fuel, steam and feed-water flow rates (as input variables). Nonlinear dynamics of the unit is investigated through the concepts of bifurcation and limit cycles behaviour. In the presence of harmonic disturbances, some coefficients of the dynamic model, fuel and steam flow rates play as the bifurcation parameters. It is shown that variation of bifurcation parameters leads to the occurrence of secondary Hopf (Neimark) and symmetry-breaking bifurcations (in drum pressure or electric output). To improve the aperiodic and quasi-periodic behaviour of the system to the stable periodic one, a control regulator is designed based on feedback linearization approach. It is shown that the controller acts efficiently in disturbance rejection and guarantees the stable periodic solutions with low oscillatory behaviour (which is essentially demanded by the power grid).

An optimal multiple-model strategy to design a controller for nonlinear processes: A boiler-turbine unit

The paper documents an optimal multiple-model strategy to design a controller for the boiler-turbine unit. There are two important problems associated with multiple-model controllers: number of models and their locations in an operating space. A method based on Vinnicombe distance is used to find minimum number of local models. First the stability of the control scheme is verified in theory. Using the closed-loop stability condition the minimum number of models is found and the models are located in a space of an unknown parameter. The performance of the proposed controller is evaluated in simulation and compared with a PI controller designed using H∞ approach and an MPC-based controller in the literature. The designed controller based on the linear local models can ensure satisfactory performance. The novel idea of this paper is the optimal strategy finding minimum number of local models in order to reduce the computational cost and processing time.

Direct Nyquist array design of PID controllers for boiler-turbine units based on gain and phase margins

In this paper, a direct Nyquist array (DNA) method for the design of PID controllers for multivariable boiler-turbine units with specifications of gain and phase margins is proposed. The essential objective is to propose a method for the design and auto-tuning of both straightforward and robust PID controllers that can be more easily implemented for the boiler-turbine units in coal-fired power generation plants in the same framework. For this purpose, the model of the original multi-input multi-output (MIMO) system is first converted into a diagonal/diagonal dominance matrix after the system is appropriately compensated. Then, various PID controller design methods for single-input single-output (SISO) systems can be easily extended to decoupled or quasi-decoupled MIMO systems. In particular, the proposed method allows the user to specify the robustness and other key performances of the system through the gain and phase margins specifications. Illustrative example is given to show the design procedure and to compare our method with other existing tuning rules.

Coordinated controller tuning of a boiler turbine unit with new binary particle swarm optimization algorithm

Coordinated controller tuning of the boiler turbine unit is a challenging task due to the nonlinear and coupling characteristics of the system. In this paper, a new variant of binary particle swarm optimization (PSO) algorithm, called probability based binary PSO (PBPSO), is presented to tune the parameters of a coordinated controller. The simulation results show that PBPSO can effectively optimize the control parameters and achieves better control performance than those based on standard discrete binary PSO, modified binary PSO, and standard continuous PSO.

Non-linear modelling of drum-boiler-turbine unit using an evolving Takagi-Sugeno fuzzy model

The boiler-turbine unit (BTU) is a highly non-linear, multivariable and time-varying system. The normal linear or quasi-linear modelling cannot reflect the real non-linear characteristics of the BTU, degrading control precision and operating performance. This paper deals with non-linear modelling of a drum-type BTU using an evolving Takagi-Sugeno (T-S) fuzzy model. A novel method based on fuzzy clustering, least-squares and genetic algorithms (GA) is proposed to construct a 'parsimonious' dynamic T-S fuzzy model with high generalisation ability. In this method, a self-organising fuzzy model generation strategy based on GA is proposed for selecting the optimal structure (including the number of rules and input variables) and antecedent parameters of the fuzzy model. Furthermore, the modified Akaike information criterion is introduced as the evaluation function of GA, which enables the self-organising strategy to choose an optimal fuzzy model with a good trade-off between fitting the training data and keeping the model simple. The simulation results show that the developed dynamic T-S fuzzy model can accurately approximate the global behaviour of the non-linear physical model with a low number of rules and fewer input variables. Further, based on the obtained T-S fuzzy model, valid control strategy studies such as predictive control can be developed.

Backstepping-based nonlinear adaptive control for coal-fired utility boiler–turbine units

The control system of boiler–turbine unit plays an important role in improving efficiency and reducing emissions of power generation unit. The nonlinear, coupling and uncertainty of the unit caused by varying working conditions should be fully considered during the control system design. This paper presents an efficient control scheme based on backstepping theory for improving load adaptability of boiler–turbines in wide operation range. The design process of the scheme includes model preprocessing, control Lyapunov functions selection, interlaced computation of adaptive control laws, etc. For simplification and accuracy, differential of steam pipe inlet pressure and integral terms of target errors are adopted. Also, to enhance practicality, implementation steps of the scheme are proposed. A practical nonlinear model of a 500 MW coal-fired boiler–turbine unit is used to test the efficiency of the proposed scheme in different conditions.

A Study of Nonlinear Control Schemes for A Boiler-Turbine Unit

Advanced control is crucial for safe and efficient operations of power plants, especially in the presence of fast and large load changes. This paper studies the load change control problem for a 160MW boiler-turbine unit. Two schemes are proposed to effectively control the boilerturbine unit that has various constraints on the system states, outputs, control input and control rate. By taking advantage of the nonlinearities of the boiler-turbine unit, we design a nonlinear state feedback controller. With a careful selection of the controller gains, the states and control inputs can be guaranteed to be within the required physical constraints. Practically, lower and upper bounds on the system outputs are also imposed to prevent the critical variables, such as drum water level, moving beyond the physical limits. To further incorporate the constraints on the system outputs as well as control-input rates into feedback design, we utilize the moving horizon control strategy. The simulations of two control methods demonstrate the well-controlled performances of the boiler-turbine unit under large and fast load changes.

Guaranteed cost nonlinear tracking control of a boiler-turbine unit: an LMI approach

This article addresses the problem of designing a guaranteed cost nonlinear state feedback tracking control for a boiler-turbine unit. First, the nonlinear boiler-turbine is re-expressed as a linear system with norm bounded uncertainties via a nonlinear transformation function. Then, based on this linear model a sufficient condition for the existence of a guaranteed cost nonlinear state feedback tracking control is derived in terms of linear matrix inequalities. The advantage of the proposed tracking control design is that only a simple nonlinear controller is constructed and it does not involve feedback linearisation technique and complicated adaptive or fuzzy schemes. An industrial boiler-turbine system is used to illustrate the effectiveness of the proposed design as compared with a linearised approach.