An adaptive feedback linearization strategy for variable speed wind energy conversion systems

This paper presents a control strategy based on adaptive feedback linearization intended for variable speed grid‐connected wind energy conversion systems (WECS). The proposed adaptive control law accomplishes energy capture maximization by tracking the wind speed fluctuations. In addition, it linearizes the system even in the presence of turbine model uncertainties, allowing the closed‐loop dynamic behaviour to be determined by a simple tuning of the controller parameters. Particularly, the attention is focused on WECS with slip power recovery, which use a power conversion stage as a rotor‐controlled double‐output induction generator. However, the concepts behind the proposed control strategy are general and can be easily extended to other WECS configurations. Copyright © 2000 John Wiley & Sons, Ltd.     

Linear models‐based LPV modelling and control for wind turbines

The non‐linear behaviour of wind turbines demands control strategies that guarantee the robustness of the closed‐loop system. Linear parameter‐varying (LPV) controllers adapt their dynamics to the system operating points, and the robustness of the closed loop is guaranteed in the controller design process. An LPV collective pitch controller has been developed within this work to regulate the generator speed in the above rated power production control zone. The performance of this LPV controller has been compared with two baseline control strategies previously designed, on the basis of classical gain scheduling methods and linear time‐invariant robust H_∞ controllers. The synthesis of the LPV controller is based on the solution of a linear matrix inequalities system, proposed in a mixed‐sensitivity control scenario where not only weight functions are used but also an LPV model of the wind turbine is necessary. As a contribution, the LPV model used is derived from a family of linear models extracted from the linearization process of the wind turbine non‐linear model. The offshore wind turbine of 5 MW defined in the Upwind European project is the used reference non‐linear model, and it has been modelled using the GH Bladed 4.0 software package. The designed LPV controller has been validated in GH Bladed, and an exhaustive analysis has been carried out to calculate fatigue load reductions on wind turbine components, as well as to analyse the load mitigation in some extreme cases. Copyright © 2014 John Wiley & Sons, Ltd.     

Design of linear controllers applied to an ethanol steam reformer for PEM fuel cell applications

This paper focuses on the design of a controller for a low temperature ethanol steam reformer for the production of hydrogen to feed a protonic exchange membrane (PEM) fuel cell. It describes different control structures for the reformer and treats the control structure selection of this multiple input multiple output (MIMO) system. For each considered control structure, decentralised 2 × 2 controllers with proportional integral (PI) control actions in each control loop are implemented. The tuning of the PI parameters and the performance evaluation of the different controllers are based on a non-linear simulation model. For the validation and comparison of the considered controllers, the dynamic response for different setpoint changes and initial conditions is analysed, as well as the behaviour of the controlled system against disturbances.     

A cost‐effective operating strategy to reduce energy consumption in a HVAC system

The operation of the building heating, ventilating, and air conditioning (HVAC) system is a critical activity in terms of optimizing the building's energy consumption, ensuring the occupants' comfort, and preserving air quality. The performance of HVAC systems can be improved through optimized supervisory control strategies. Set points can be adjusted by the optimized supervisor to improve the operating efficiency. This paper presents a cost‐effective building operating strategy to reduce energy costs associated with the operation of the HVAC system. The strategy determines the set points of local‐loop controllers used in a multi‐zone HVAC system. The controller set points include the supply air temperature, the supply duct static pressure, and the chilled water supply temperature. The variation of zone air temperatures around the set point is also considered. The strategy provides proper set points to controllers for minimum energy use while maintaining the required thermal comfort. The proposed technology is computationally simple and suitable for online implementation; it requires access to some data that are already measured and therefore available in most existing building energy management and control systems. The strategy is evaluated for a case study in an existing variable air volume system. The results show that the proposed strategy may be an excellent means of reducing utility costs associated with maintaining or improving indoor environmental conditions. It may reduce energy consumption by about 11% when compared with the actual strategy applied on the investigated existing system. Copyright © 2007 John Wiley & Sons, Ltd.     

Cascade closed-loop control of solar trackers applied to HCPV systems

High concentration photovoltaic (HCPV) modules require a high precision tracking system for reaching their highest conversion efficiency. One way to accomplish this goal is by using a closed-loop mechanism and a sun sensor to track the sunlight. This paper proposes a cascade control algorithm capable of achieving a sun tracking error of 1′ for its application in high concentration photovoltaic systems. The algorithm follows an inner loop-outer loop topology. The inner loop employs a Nonlinear Proportional-Proportional Integral (NP-PI) controller and the outer loop resorts on a Proportional Integral (PI) controller. A tuning procedure for setting up the cascade controller is also described. Experiments on a laboratory prototype compare the performance of the proposed cascade controller with a PI controller not resorting on an inner loop. These outcomes show that the proposed control law provides improved tracking accuracy with less actuator wear.     

A decentralized adaptive controller for multimachine power systems

This paper presents a new adaptive controller via multilevel technique. The control strategy is based on decomposing control signals into two components: the first one balances the effect of interconnections between the subsystems, while the second one is a local adaptive controller based on hyperstability theory for the decentralized subsystems. The changeable gains generated by a non‐linear time‐varying function act as the adaptive mechanism. Compared with MRAC or STAC the proposed control avoids the difficulty in choosing an appropriate reference model and the burden of implementing an online parameter estimator. The local control is constructed so that the closed‐loop system is hyperstable guaranteeing the dynamic stability improvement of each subsystem in the multimachine power system. A guarantee of stability of the overall system is also given. Simulation results of a numerical example of a multimachine power system reveal that the low frequency oscillations can completely be eliminated using the proposed control scheme. Copyright © 2000 John Wiley & Sons, Ltd.     

An adaptive sliding mode observer based near-optimal OER tracking control approach for PEMFC under dynamic operation condition

Tracking control of oxygen excess ratio (OER) is crucial for dynamic performance and operating efficiency of the proton exchange membrane fuel cell (PEMFC). OER tracking errors and overshoots under dynamic load limit the PEMFC output power performance, and also could lead oxygen starvation which seriously affect the life of PEMFC. To solve this problem, an adaptive sliding mode observer based near-optimal OER tracking control approach is proposed in this paper. According to real time load demand, a dynamic OER optimization strategy is designed to obtain an optimal OER. A nonlinear system model based near-optimal controller is designed to minimize the OER tracking error under variable operation condition of PEMFC. An adaptive sliding mode observer is utilized to estimate the uncertain parameters of the PEMFC air supply system and update parameters in near-optimal controller. The proposed control approach is implemented in OER tracking experiments based on air supply system of a 5 kW PEMFC test platform. The experiment results are analyzed and demonstrate the efficacy of the proposed control approach under load changes, external disturbances and parameter uncertainties of PEFMC system.     

直流微电网系统的DC/DC变换器控制系统设计

全桥DC/DC变换器由于具有高功率密度、高效率、高变压比及电气隔离的特点,成为直流微电网系统中重要的电力电子接口。而移相全桥DC/DC变换器具有高阶时变非线性的特点,具体应用时较难建立其精确的数学模型,这影响了传统PID控制性能,因此设计了模糊自整定控制器。通过对峰值电流模式下变换器的小信号建模,在传统PI控制的基础上,给出了基于模糊理论的PI参数在线自整定方法。同时,利用Matlab仿真工具给出了模糊控制器的设计方法,并通过DSP对其进行软硬件实现。仿真和试验结果表明,模糊自整定控制与常规PI控制相比,提高了系统的抗扰动能力,改善了系统的动态性能,从而提高了整个微电网系统的可靠性。     

Dynamic model of an HVAC system for control analysis

This paper describes a procedure for deriving a dynamic model of an HVAC system that consists of a zone, heating coil, cooling and dehumidifying coil, humidifier, ductwork, fan, and mixing box. In particular, the interest is centered on control strategies to reduce energy consumption and improving the quality of the indoor environment. Indoor temperature and humidity may be maintained at set point values by an air-handling unit using a PID control action. The PID parameters must be carefully tuned to produce less oscillatory responses. The tuning technique, using the Ziegler-Nichols rule, is investigated from a practical viewpoint. Simulation results showing the open loop and the closed loop responses of indoor temperature and humidity ratio are given. The results show that the system is capable of controlling the disturbance efficiently within a small period of time and with less error. The dynamic model can be especially useful for control strategies that require knowledge of the dynamic characteristics of HVAC systems.     

储能系统双向Buck-Boost变换器控制策略研究

为应对可再生能源出力波动引起储能系统功率流动方向的频繁变化,提出一种基于自抗扰控制和模型预测控制（ADRC+MPC）的储能系统双向Buck-Boost变换器控制策略。其中模型预测控制方法应用于电流内环,无需进行参数整定的同时,也提高了系统的响应速度;采用自抗扰控制策略的电压外环,通过在高频段降阶简化控制对象,达到降低自抗扰控制器复杂度的目的。仿真和样机实验显示当电感电流与输出电压参考值突变时,系统可分别在0.2与30 ms内迅速调整到给定值;当负载与电源电压突变时,系统能在20 ms内恢复稳定。实验结果证明该文提出的控制方法优于PI+MPC策略,具有响应速度快、超调量和波动幅度小的特点。     

Adaptive fuzzy sliding-mode control for induction servomotor systems

An adaptive fuzzy sliding-mode control design method is proposed for induction servomotor system control. The proposed adaptive fuzzy sliding-mode control system is comprised of a fuzzy controller and a compensation controller. The fuzzy controller is the main tracking controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the fuzzy controller. A tuning methodology is derived to tune the premise and consequence parts of the fuzzy rules. The online tuning algorithm is derived in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Moreover, to relax the requirement for the uncertain bound in the compensation controller, an estimation mechanism is investigated to observe the uncertain bound, so that the chattering phenomena of the control efforts can be relaxed. To illustrate the effectiveness of the proposed design method, a comparison between a conventional fuzzy control and the proposed adaptive fuzzy sliding-mode control is made. Simulation and experimental results verify that the proposed adaptive fuzzy sliding-mode control design method can achieve favorable control performance with regard to parameter variations and external disturbances.     

基于模糊自适应PID的锅炉汽包水位智能控制系统

针对锅炉汽包水位经常受到负荷变化、进出水速度、水质等诸多因素的影响,具有时滞、非线性等特性,设计了以误差e及误差变化率ec为输入,PID控制器的KP、KI、KD为输出的二输入三输出的模糊自适应PID控制器,目的是为了改善PID控制的参数整定困难、适应差的缺点。并通过仿真进行了验证,结果表明锅炉汽包水位控制系统不论是在负荷变化较小的情况下,还是在负荷剧烈变化的运行工况下,都可以实现水位的平稳调节,水位始终保持在规定的波动范围之内。     

Modeling,optimization, and control of microbial electrolysis cells in a fed‐batch reactor for production of renewable biohydrogen gas

An integrated modeling, optimization, and control approach for the design of a microbial electrolysis cell (MEC) was studied in this paper. Initially, this study describes the improvement of the mathematical MEC model for hydrogen production from wastewater in a fed‐batch reactor. The model, which was modified from an already existing model, is based on material balance with the integration of bioelectrochemical reactions describing the steady‐state behavior of biomass growth, consumption of substrates, hydrogen production, and the effect of applied voltage on the performance of the MEC fed‐batch reactor. Another goal of this work is to implement a suitable control strategy to optimize the production of biohydrogen gas by selecting the optimal current and applied voltage to the MEC. Various simulation tests involving multiple set‐point changes, disturbance rejection, and noise effects were performed to evaluate the performance where the proposed proportional–integral–derivative control system was tuned with an adaptive gain technique and compared with the Ziegler–Nichols method. The simulation results show that optimal tuning can provide better control effect on the MEC system, where optimal H₂ gas production for the system was achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Preview predictive control layer design based upon known wind turbine blade‐pitch controllers

The use of upstream wind measurements has motivated the development of blade‐pitch preview controllers for improving rotor speed tracking and structural load reduction beyond that achievable via conventional feedback control. Such preview controllers, typically based upon model predictive control (MPC) for its constraint handling properties, alter the closed‐loop dynamics of the existing blade‐pitch feedback control system. This can result in a deterioration of the robustness properties and performance of the existing feedback control system. Furthermore, performance gains from utilising the upcoming real‐time measurements cannot be easily distinguished from the feedback control, making it difficult to formulate a clear business case for the use of preview control. Therefore, the aim of this work is to formulate a modular MPC layer on top of a given output‐feedback blade‐pitch controller, with a view to retaining the closed‐loop robustness and frequency‐domain performance of the latter. The separate nature of the proposed controller structure enables clear and transparent quantification of the benefits gained by using preview control, beyond that of the underlying feedback controller. This is illustrated by results obtained from high‐fidelity closed‐loop turbine simulations, showing the proposed control scheme incorporating knowledge of the oncoming wind and constraints achieved significant 43% and 30% reductions in the rotor speed and flap‐wise blade moment standard deviations, respectively. Additionally, the chance of constraint violations on the rotor speed decreased remarkably from 2.15% to 0.01%, compared to the nominal controller. Copyright © 2017 John Wiley & Sons, Ltd.     

Bilateral based robust load frequency control

Load frequency control (LFC) has been one of the major subjects in electric power system design/operation and is becoming much more significant today in accordance with increasing size and the changing structure and complexity of interconnected power systems. In practice, power systems use simple proportional-integral (PI) controllers for frequency regulation and load tracking. However, since the PI controller parameters are usually tuned based on classical or trial and error approaches, they are incapable of obtaining good dynamical performance for a wide range of operating conditions and various load changes scenarios in a restructured power system.This paper addresses a new decentralized robust LFC design in a deregulated power system under a bilateral based policy scheme. In each control area, the effect of bilateral contracts is taken into account as a set of new input signals in a modified traditional dynamical model. The LFC problem is formulated as a multi-objective control problem via a mixed H₂/H_∞ control technique. In order to design a robust PI controller, the control problem is reduced to a static output feedback control synthesis, and then, it is solved using a developed iterative linear matrix inequalities algorithm to get a robust performance index close to a specified optimal one. The proposed method is applied to a 3 control area power system with possible contract scenarios and a wide range of load changes. The results of the proposed multi-objective PI controllers are compared with H₂/H_∞ dynamic controllers.     

Adaptive self-tuning MTPA vector controller for IPMSM drive system

This paper presents an adaptive self-tuning maximum torque per ampere (MTPA) vector controller for an interior permanent-magnet synchronous motor (IPMSM) drive system. The control scheme consists of a synchronous frame decoupling current controller, MTPA torque controller, and adaptive parameter estimator. The estimator is applied to the q-axis current dynamics as the d-axis inductance can be assumed to be constant without loss of accuracy. Since the q-axis current dynamics is being disturbed by the magnet's back-EMF voltage, the proposed estimator is combined with a robust active-state decoupling scheme to ensure unbiased parameter estimate. The robust decoupling scheme is realized by estimating the magnet's flux linkage by a simple adaptation algorithm based on the steepest descent method. The system's model is greatly simplified when the robust decoupling scheme is combined with the q-axis current dynamics. Relying on the simplified model, a natural adaptive observer is used to estimate the q-axis current. Unknown motor parameters are estimated by minimizing the state estimation error using an iterative gradient algorithm offered by the affine projection. The estimated parameters are used for the self-tuning control. Experimental results are presented to demonstrate the validity and usefulness of the online parameter estimation and control loop tuning technique.     

Adaptive tower damping control for offshore wind turbines

This paper deals with the problem of wind turbine tower damping control design and implementation in situations where the support structure parameters vary from their nominal design values. Such situations can, in practice, occur for onshore and especially offshore wind turbines and are attributed to aging, turbine installation, scour or marine sand dunes phenomena and biofouling. Practical experience of wind turbine manufacturing industry has shown that such effects are most easily quantified in terms of the first natural frequency of the turbine support structure. The paper brings forward a study regarding the amount to which nominal tower damping controller performance is affected by changes in the turbine natural frequency. Subsequently, an adaptive tower damping control loop is designed using linear parameter‐varying control synthesis; the proposed tower damping controller depends on this varying parameter which is assumed throughout the study to be readily available. An investigation of the fatigue load reduction performance in comparison with the original tower damping control approach is given for a generic three‐bladed horizontal‐axis wind turbine. Copyright © 2016 John Wiley & Sons, Ltd.     

具有大延迟特性的热工过程的改进PI控制器

本文提出了一种对具有大延迟特性的热工过程的改进ＰＩ控制,这种控制器实际是Ｓｍｉｔｈ预估控制的一个特例。但在设计这种控制器之前,可以不对过程的数学模型有个精确了解,控制参数也可以象ＰＩ控制器的参数一样通过现场运行进行调整,具有广泛应用于过程控制的潜力。     

A strategy for the spatial temperature control of a molten carbonate fuel cell system

The object of the paper is to develop a simple and practical control strategy for a molten carbonate fuel cell (MCFC) system. Based on a dynamic model and the control demand, a cascade control strategy is designed. The master controller imposes a change of cell current representing a change in power demand and sets the amount of fuel gas, the steam-to-carbon ratio, the air number and the cathode gas recycle ratio to their corresponding conditions for optimal steady state electric efficiency. Two feedback PID controllers are in the inner loop, one guarantees the solid temperature not to exceed a maximum temperature by changing the air number around the default set by the master controller; the other controls the maximum temperature difference by adjusting the steam-to-carbon ratio. Step response tests show that this control strategy works well when the cell current changes.     

DESIGN AND TUNING OF A FUZZY CONTROLLER FOR INDOOR AIR QUALITY AND THERMAL COMFORT MANAGEMENT

This paper presents the development and testing of a multi objective fuzzy controller. It is dedicated to the control of thermal comfort and indoor air quality while minimising energy consumption and reducing instabilities are other constraints for this controller. After a brief introduction on the difficult task of indoor climate control, the test cell and its corresponding model is described in the second section. The model has been developed within TRNSYS. Section 3 describes the architecture of the fuzzy controller applied to these control objectives in the test cell. A hierarchical architecture has finally been selected since it is a very flexible architecture and it results in reducing the total number of fuzzy rules. The rule optimisation technique, based on genetic algorithms is also presented in the third section. Simulation results are finally presented. They prove that, after optimisation, the fuzzy controller greatly outperforms a typical ON-OFF controller on all control criteria. Energy consumption is in particular reduced by more than 10%. The fourth section of this chapter presents field experiments among 20 subjects of both ON-OFF control and fuzzy control. If major differences are not observed on the thermal comfort and indoor air quality point of view, these experiments however illustrate the importance of on-line tuning of specific fuzzy rules.