Multivariable adaptive control of the bead profile geometry in gas metal arc welding with thermal scanning

This research implements the newly introduced scan welding technique in processes with material deposition. A laboratory station is developed with robotic plasma-arc welding under infrared pyrometry sensing for thermal scanning, and with gas metal arc welding under laser profilometry feedback for material transfer. The dynamics of the weld profile geometry (i.e. the bead width and reinforcement height) are modeled experimentally with respect to the process conditions (weld speed and wire feed). This model serves as the basis for the development of a simple geometry feedback control scheme. A multivariable adaptive control system, based on a generalized one step ahead regulation algorithm is also established and validated experimentally. Application of such bead profile regulation is explored in multipass weld joining, orbital welding, coating hardfacing and rapid manufacturing methods.     

Multivariable 2-sliding mode control for a wind energy system based on a double fed induction generator

The purpose of this paper is to present a control strategy using Multiple Input/Multiple Output (MIMO) Second Order Sliding Modes (SOSM) for a grid-connected variable-speed Wind Energy Conversion System (WECS). The latter is based on a Double Fed Induction Generator (DFIG) in a bidirectional configuration with slip power recovery. Its points of operation can be electronically controlled and, with them, two independent control objectives can be stated. Thus, a control is designed to maximize the energy captured from the wind and to regulate the stator reactive power, contributing to the compensation of the power factor according to grid requirements.     

One-step-ahead adaptive control of a wind-driven,synchronous generator system

Control of a wind power plant as an isolated power source is analyzed. The plant consists of a wind turbine (connected by means of a gear box to a three-phase synchronous electric generator) and a control system. Mathematical models of the wind turbine and electrical generator have been proposed. The one-step-ahead adaptive control technique has been adopted to govern the system. Results of a control test case are shown in order to demonstrate the reliability of the proposed control technique.     

Stabilizing control of a high-order generator model by adaptive feedback linearization

We present an adaptive feedback linearizing control scheme for excitation control and power system stabilization. The power system is a synchronous generator which is first modeled as an input-output nonlinear discrete-time system approximated by two neural networks. Then, the controller is synthesized to adaptively compute an appropriate feedback linearizing control law at each sampling instant using estimates provided by the neural system model. This formulation simplifies the problem to that of designing a linear pole-placement controller which is itself not a neural network but is adaptive in the sense that the neural estimator adapts itself online. Additionally, the requirement for exact knowledge of the system dynamics, full state measurement, as well as other difficulties associated with feedback linearizing control for power systems are avoided in this approach. Simulations demonstrate its application to a high-order single-machine system under various conditions.     

Multivariable robust PID control for a PEMFC system

This paper proposes robust proportional-integral-derivative (PID) control for a proton exchange membrane fuel cell (PEMFC) system. We model a PEMFC as a multivariable system, and apply identification techniques to obtain the system’s transfer function matrices, where system variations and disturbances are regarded as uncertainties. Because robust control can cope with system uncertainties and disturbances, it has been successfully applied to improve the stability, performance, and efficiency of PEMFC systems in previous studies. However, the resulting robust controllers might be too complicated for hardware implementation. On the other hand, PID control has been widely applicable to engineering practices because of its simple structure, but it lacks stability analysis for systems with uncertainties. Therefore, by combining the merits of robust control and PID control, we design robust PID controllers for the PEMFC system. Based on evaluation of stability, performance, and efficiencies, the proposed robust PID controllers are shown to be effective.     

Multivariable robust control of a power plant deaerator

The design of a robust controller for the deaerator of the Experimental Breeder Reactor-II (EBR-II) that uses the linear quadratic Gaussian with loop transfer recovery (LQG/LTR) procedure is described. At present, classical proportional-integral (PI) controllers are used to control the deaerator. When the operating condition changes, the system is disturbed, or a fault occurs, and the PI controllers may fail to maintain the desired performance. A robust controller that can accommodate system faults and obtain a reasonable behavior for a wide range of model uncertainty was designed. The controller provides the desired performance despite a considerable change in the operating condition, accommodates some of the failures that can occur, and provides the choice of penalizing one variable over another. The design is tested for robustness by varying the system operating conditions and simulating a steam valve failure. The set of nonlinear simulations using the modular modeling system and the advanced continuous simulation language is included     

Multivariable generalized predictive control of a boiler system

An application of a multiloop generalized predictive control (GPC) scheme to achieve self-tuning control of superheat pressure and steam temperatures in a 200 MW power station drum boiler are presented. Controllers have been designed and evaluated using a detailed nonlinear boiler model which is well established and validated. Results illustrating the performance of the plant with GPC are presented and compared with conventional PI control. The results show that substantial improvements in control can be achieved with the GPC. Steam pressure and temperature variations are greatly reduced, without offsets, and with less controller activity     

A model study for cyclic thermal loading and thermal performance of a thermoelectric generator

Thermal cyclic loading influences the life cycle of the thermoelectric device pins because of the thermal stress developed in the pins. Although thermal efficiency improves for different geometric configurations of the device pins, development of thermal stresses limit the selection of pin geometry in practical applications, particularly under cyclic thermal loading. Consequently, in the present study, thermal stress analysis of thermoelectric pins under cyclic thermal loading is carried out. The influence of thermoelectric pin geometry on the stress levels is examined when the device is subjected to the thermal cyclic loading. The predictions of thermal stress distribution are validated with the data presented in the open literature. It is found that pin geometric configuration has a significant effect on the stress levels developed in the pin when subjected to cyclic thermal loading. The pin configuration R_A = 1 (parallel pins) results in the minimum value of the maximum von Mises stress in the pins as compared to that corresponding to other configurations. Copyright © 2014 John Wiley & Sons, Ltd.     

Voltage-frequency control of a self-excited induction generator

A new strategy for controlling voltage and frequency of a self excited induction generator (SEIG) is presented. The SEIG operates in the linear region of the core magnetizing curve, so that efficiency and performance are upgraded. An external excitation circuit, comprising permanently connected capacitors and electronically switched inductances is used. The external circuit allows to compensate for the generator reactive demand. A detailed analysis is performed, showing some salient aspects related to the connection of the external excitation circuit on the control performance. Asynchronous switching is used, but some important considerations must be taken into account related to the instantaneous phase angle between stator voltage and external inductor current at the switching instant, if good transient response is desired. Sliding mode controllers are proposed, showing good dynamic response and robust behavior upon changes in load and generator parameters. Computer simulations are used to demonstrate the validity of the proposed scheme     

An adaptive neuro-control system of synchronous generator for powersystem stabilization

This paper proposes a nonlinear adaptive generator control system using neural networks, called an adaptive neuro-control system (ANCS). This system generates supplementary control signals to conventional controllers and works adaptively in response to changes in operating conditions and network configuration. Through digital time simulations for a one-machine infinite bus test power system, the control performance of the ANCS and advanced controllers such as a linear optimal regulator and a self-tuning regulator is evaluated from the viewpoint of stability enhancement. As a result, the proposed ANCS using neural networks with nonlinear characteristics improves system damping more effectively and more adaptively than the other two controllers designed for the linearized model of the power system     

Multivariable control algorithm for laboratory experiments in wind energy conversion

Advanced experimentation with wind energy conversion systems is described. The real time multivariable control of a wind turbine is designed for investigation of theoretical concepts and their physical implementation. The control system includes a speed controller and a disturbance estimator for enhanced robustness of the control system. In order to provide students with deeper understanding of wind energy and energy extraction, a maximum power point tracking algorithm is developed and integrated into the control system. The multivariable control system is implemented in a small wind turbine laboratory system. A power electronic interface is based on two DC–DC converters: a buck converter for control of the speed and a boost converter controlling the load voltage. Experimental results demonstrate effectiveness of the multivariable control system for a wind turbine providing maximum power extraction. The experiment can be reconfigured for teaching various control concepts to both undergraduate and graduate students.     

A comparative study between linear and sliding mode adaptive controllers for a hot gas generator

A hot gas generator is a compact heat exchanger that produces high temperature or enthalpy gases. This paper presents two methods for controlling the system. The first one is an adaptive sliding mode controller that is a Lyapunov based method and proposed to confront the dynamic modeling deficiencies and system uncertainties. The second one is a linear adaptive controller that gives a new attractive ability to the system which can track a complicated requested path. Each of the presented controllers has some capabilities that may be preferred to other. In this paper, these methods are extensively compared by several transient inputs. On the other hand, since heat exchangers are typically uncertain systems, a robust controller is necessary to apply on them. Therefore, robustness is another criterion for the comparison of the mentioned controllers. By considering the results of this comparison, one could be aware of the application domain of each controller.     

Multivariable robust control of a proton exchange membrane fuel cell system

This paper applies multivariable robust control strategies to a proton exchange membrane fuel cell (PEMFC) system. From the system point of view, a PEMFC can be modeled as a two-input-two-output system, where the inputs are air and hydrogen flow rates and the outputs are cell voltage and current. By fixing the output resistance, we aimed to control the cell voltage output by regulating the air and hydrogen flow rates. Due to the nonlinear characteristics of this system, multivariable robust controllers were designed to provide robust performance and to reduce the hydrogen consumption of this system. The study was carried out in three parts. Firstly, the PEMFC system was modeled as multivariable transfer function matrices using identification techniques, with the un-modeled dynamics treated as system uncertainties and disturbances. Secondly, robust control algorithms were utilized to design multivariable H_∞ controllers to deal with system uncertainty and performance requirements. Finally, the designed robust controllers were implemented to control the air and hydrogen flow rates. From the experimental results, multivariable robust control is shown to provide steady output responses and significantly reduce hydrogen consumption.     

Network power flux control of a wind generator

In this paper, a network power flux control of a variable speed wind generator is investigated. The wind generator system consists of a doubly fed induction generator (DFIG) connected to the network associated to a flywheel energy storage system (FESS). The dynamic behaviour of a wind generator, including the models of the wind turbine, the doubly fed induction generator, the back-to-back AC/AC converter, the converter control and the power control of this system, is studied. Is also investigated a control method of the FESS system which consists of the classical squirrel-cage induction machine (IM) supplied off the variable speed wind generator (VSWG). In order to verify the validity of the proposed method, a dynamic model of the proposed system has been simulated, for different operating points, to demonstrate the performance of the system.     

Understanding modern generator control

A simple discussion about generator control without bode plots and other sophisticated references necessary to equipment design is presented. Two kinds of control schemes used for most generator drives, droop control, and frequency control are discussed. Synchronous and induction generators, and their differences in control, are also discussed. The operation of generators both connected to and disconnected from the utility grid is also examined     

A thermal cycling type test for generator stator winding insulation

A test has been designed and implemented which cycles the temperature between 40°C and 150°C in about 80 min by the use of circulating currents and cooling air. The test has been successfully used to evaluate the relative performance of similar stator bars made by three different manufacturers. The thermal cycling test was able to duplicate the insulation delamination process and presumably those insulation systems which performed well in the thermal cycling test could last longer in service. In addition to being used for pumped-storage generators, the thermal cycling test may be useful to evaluate the insulation system in combustion turbine generators     

Multivariable control strategy for variable speed, variable pitch wind turbines

Reliable and powerful control strategies are needed for wind energy conversion systems to achieve maximum performance. A new control strategy for a variable speed, variable pitch wind turbine is proposed in this paper for the above-rated power operating condition. This multivariable control strategy is realized by combining a nonlinear dynamic state feedback torque control strategy with a linear control strategy for blade pitch angle. A comparison with existing strategies, PID and LQG controllers, is performed. The proposed approach results in better power regulation. The new control strategy has been validated using an aeroelastic wind turbine simulator developed by NREL for a high turbulence wind condition.     

Coordinated control strategy for a PV-storage grid-connected system based on a virtual synchronous generator

Due to the characteristics of intermittent photovoltaic power generation and power fluctuations in distributed photovoltaic power generation, photovoltaic grid-connected systems are usually equipped with energy storage units. Most of the structures combined with energy storage are used as the DC side. At the same time, virtual synchronous generators have been widely used in distributed power generation due to their inertial damping and frequency and voltage regulation. For the PV-storage grid-connected system based on virtual synchronous generators, the existing control strategy has unclear function allocation, fluctuations in photovoltaic inverter output power, and high requirements for coordinated control of PV arrays, energy storage units, and photovoltaic inverters, which make the control strategy more complicated. In order to solve the above problems, a control strategy for PV-storage grid-connected system based on a virtual synchronous generator is proposed. In this strategy, the energy storage unit implements maximum power point tracking, and the photovoltaic inverter implements a virtual synchronous generator algorithm, so that the functions implemented by each part of the system are clear, which reduces the requirements for coordinated control. At the same time, the smooth power command is used to suppress the fluctuation of the output power of the photovoltaic inverter. The simulation validates the effectiveness of the proposed method from three aspects: grid-connected operating conditions, frequency-modulated operating conditions, and illumination sudden-drop operating condition. Compared with the existing control strategies, the proposed method simplifies the control strategies and stabilizes the photovoltaic inverter fluctuation in the output power of the inverter.     

Power variation control of a wind generator by using feed forward control

The pitch control of wind generators is usually made by a feed back control concept. However, under the conditions where a wind speed changes very frequently due to geographic reasons of the site and the target system has large rotor inertia, the feed back signal which is applied to the control system to compensate disturbance such as wind speed variations is delayed, and consequently the control strategy to keep the generated power at a constant value does not work well. If the wind speed shows too much variation, this will cause a violent variation of power and result in step out operation of the generator from the power system due to magnetic saturation. This paper proposes a control strategy to reduce the power variations by introducing feed forward control combining with the conventional feed back control.     

Adaptive fuzzy logic control of a turbine generator system

This paper is concerned with the application of an adaptive, fuzzy logic controller to a synchronous generator system. Significant reductions in the amount of required calculations have been made which allow a direct analysis of the system. A novel on-line training algorithm is proposed to adapt fuzzy rule base which is shown to converge globally and provide the desired regulation for disturbances at all operating points. The sensitivity of the controller with respect to changes in design parameters is analysed. Test responses are compared with a self-tuning regulator to show the effectiveness of the proposed system. Micromachine tests further establish the possibility of developing a practical controller