Fuzzy Control System for Voltage Regulation In Power Transformers

A fuzzy control strategy for voltage regulation in electric power distribution systems is introduced in this article. This real-time controller would act on power transformers equipped with under-load tap changers. The fuzzy system was employed to turn the voltage-control relays into adaptive devices. The scope of the present study has been limited to the power distribution substation, and both the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage control strategies that satisfy both the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. A prototype based on the fuzzy control strategy proposed in this paper has also been implemented for validation purposes and its experimental results were highly satisfactory.

Active sound quality control of engine induced cavity noise

Active control solutions appear to be a feasible approach to cope with the steadily increasing requirements for noise reduction in the transportation industry. Active controllers tend to be designed with a target on the sound pressure level reduction. However, the perceived control efficiency for the occupants can be more accurately assessed if psychoacoustic metrics can be taken into account. Therefore, this paper aims to evaluate, numerically and experimentally, the effect of a feedback controller on the sound quality of a vehicle mockup excited with engine noise. The proposed simulation scheme is described and experimentally validated. The engine excitation is provided by a sound quality equivalent engine simulator, running on a real-time platform that delivers harmonic excitation in function of the driving condition. The controller performance is evaluated in terms of specific loudness and roughness. It is shown that the use of a quite simple control strategy, such as a velocity feedback, can result in satisfactory loudness reduction with slightly spread roughness, improving the overall perception of the engine sound. (C) 2008 Elsevier Ltd. All rights reserved.

Robust Control of Flight Simulator Motion Base

The purpose of this study is to apply robust inverse dynamics control for a six-degree-of-freedom flight simulator motion system. From an implementation viewpoint, simplification of the inverse dynamics control law is introduced by assuming control law matrices as constants. The robust control strategy is applied in the outer loop of the inverse dynamic control to counteract the effects of imperfect compensation due this simplification. The control strategy is designed using the Lyapunov stability theory. Forward and inverse kinematics and a full dynamic model of a six-degree-of-freedom motion base driven by electromechanical actuators are briefly presented. A describing function, acceleration step response and some maneuvers computed from the washout filter were used to evaluate the performance of the controllers.

Modeling, control and experimental validation of a novel actuator based on shape memory alloys

The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.

Robust model predictive control with zone control

Model predictive control (MPC) is usually implemented as a control strategy where the system outputs are controlled within specified zones, instead of fixed set points. One strategy to implement the zone control is by means of the selection of different weights for the output error in the control cost function. A disadvantage of this approach is that closed-loop stability cannot be guaranteed, as a different linear controller may be activated at each time step. A way to implement a stable zone control is by means of the use of an infinite horizon cost in which the set point is an additional variable of the control problem. In this case, the set point is restricted to remain inside the output zone and an appropriate output slack variable is included in the optimisation problem to assure the recursive feasibility of the control optimisation problem. Following this approach, a robust MPC is developed for the case of multi-model uncertainty of open-loop stable systems. The controller is devoted to maintain the outputs within their corresponding feasible zone, while reaching the desired optimal input target. Simulation of a process of the oil re. ning industry illustrates the performance of the proposed strategy.

A stable MPC with zone control

Several MPC applications implement a control strategy in which some of the system outputs are controlled within specified ranges or zones, rather than at fixed set points [J.M. Maciejowski, Predictive Control with Constraints, Prentice Hall, New Jersey, 2002]. This means that these outputs will be treated as controlled variables only when the predicted future values lie outside the boundary of their corresponding zones. The zone control is usually implemented by selecting an appropriate weighting matrix for the output error in the control cost function. When an output prediction is inside its zone, the corresponding weight is zeroed, so that the controller ignores this output. When the output prediction lies outside the zone, the error weight is made equal to a specified value and the distance between the output prediction and the boundary of the zone is minimized. The main problem of this approach, as long as stability of the closed loop is concerned, is that each time an output is switched from the status of non-controlled to the status of controlled, or vice versa, a different linear controller is activated. Thus, throughout the continuous operation of the process, the control system keeps switching from one controller to another. Even if a stabilizing control law is developed for each of the control configurations, switching among stable controllers not necessarily produces a stable closed loop system. Here, a stable M PC is developed for the zone control of open-loop stable systems. Focusing on the practical application of the proposed controller, it is assumed that in the control structure of the process system there is an upper optimization layer that defines optimal targets to the system inputs. The performance of the proposed strategy is illustrated by simulation of a subsystem of an industrial FCC system. (C) 2008 Elsevier Ltd. All rights reserved.

The Policy Iteration Algorithm for Average Continuous Control of Piecewise Deterministic Markov Processes

The main goal of this paper is to apply the so-called policy iteration algorithm (PIA) for the long run average continuous control problem of piecewise deterministic Markov processes (PDMP`s) taking values in a general Borel space and with compact action space depending on the state variable. In order to do that we first derive some important properties for a pseudo-Poisson equation associated to the problem. In the sequence it is shown that the convergence of the PIA to a solution satisfying the optimality equation holds under some classical hypotheses and that this optimal solution yields to an optimal control strategy for the average control problem for the continuous-time PDMP in a feedback form.

THE VANISHING DISCOUNT APPROACH FOR THE AVERAGE CONTINUOUS CONTROL OF PIECEWISE DETERMINISTIC MARKOV PROCESSES

This work is concerned with the existence of an optimal control strategy for the long-run average continuous control problem of piecewise-deterministic Markov processes (PDMPs). In Costa and Dufour (2008), sufficient conditions were derived to ensure the existence of an optimal control by using the vanishing discount approach. These conditions were mainly expressed in terms of the relative difference of the alpha-discount value functions. The main goal of this paper is to derive tractable conditions directly related to the primitive data of the PDMP to ensure the existence of an optimal control. The present work can be seen as a continuation of the results derived in Costa and Dufour (2008). Our main assumptions are written in terms of some integro-differential inequalities related to the so-called expected growth condition, and geometric convergence of the post-jump location kernel associated to the PDMP. An example based on the capacity expansion problem is presented, illustrating the possible applications of the results developed in the paper.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Prevalence of diabetic peripheral neuropathy and relation to glycemic control therapies at baseline in the BARI 2D cohort

We evaluated the associations between glycemic therapies and prevalence of diabetic peripheral neuropathy (DPN) at baseline among participants in the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) trial on medical and revascularization therapies for coronary artery disease (CAD) and on insulin-sensitizing vs. insulin-providing treatments for diabetes. A total of 2,368 patients with type 2 diabetes and CAD was evaluated. DPN was defined as clinical examination score > 2 using the Michigan Neuropathy Screening Instrument (MNSI). DPN odds ratios across different groups of glycemic therapy were evaluated by multiple logistic regression adjusted for multiple covariates including age, sex, hemoglobin A1c (HbA1c), and diabetes duration. Fifty-one percent of BARI 2D subjects with valid baseline characteristics and MNSI scores had DPN. After adjusting for all variables, use of insulin was significantly associated with DPN (OR = 1.57, 95% CI: 1.15-2.13). Patients on sulfonylurea (SU) or combination of SU/metformin (Met)/thiazolidinediones (TZD) had marginally higher rates of DPN than the Met/TZD group. This cross-sectional study in a cohort of patients with type 2 diabetes and CAD showed association of insulin use with higher DPN prevalence, independent of disease duration, glycemic control, and other characteristics. The causality between a glycemic control strategy and DPN cannot be evaluated in this cross-sectional study, but continued assessment of DPN and randomized therapies in BARI 2D trial may provide further explanations on the development of DPN.

Modeling, control and simulation of full-power converter wind turbines equipped with permanent magnet synchronous generator

In this paper, two wind turbines equipped with a permanent magnet synchronous generator (PMSG) and respectively with a two-level or a multilevel converter are simulated in order to access the malfunction transient performance. Three different drive train mass models, respectively, one, two and three mass models, are considered in order to model the bending flexibility of the blades. Moreover, a fractional-order control strategy is studied comparatively to a classical integer-order control strategy. Computer simulations are carried out, and conclusions about the total harmonic distortion (THD) of the electric current injected into the electric grid are in favor of the fractional-order control strategy.

A Pitch Control Malfunction Analysis for Wind Turbines with Permanent Magnet Synchronous Generator and Full-power Converters: Proportional Integral Versus Fractional-order Controllers

A transient analysis for two full-power converter wind turbines equipped with a permanent magnet synchronous generator is studied in this article, taking into consideration, as a new contribution to earlier studies, a pitch control malfunction. The two full-power converters considered are, respectively, a two-level and a multi-level converter. Moreover, a novel control strategy based on fractional-order controllers for wind turbines is studied. Simulation results are presented; conclusions are in favor of the novel control strategy, improving the quality of the energy injected into the electric grid.

Fractional-order control and simulation of wind energy systems with PMSG/full-power converter topology

This paper presents a new integrated model for the simulation of wind energy systems. The proposed model is more realistic and accurate, considering a variable-speed wind turbine, two-mass rotor, permanent magnet synchronous generator (PMSG), different power converter topologies, and filters. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with PMSG/full-power converter topology, based on fractional-order controllers. Comprehensive simulation studies are carried out with matrix and multilevel power converter topologies, in order to adequately assert the system performance in what regards the quality of the energy injected into the electric grid. Finally, conclusions are duly drawn.

Comparative study of power converter topologies and control strategies for the harmonic performance of variable-speed wind turbine generator systems

Power converters play a vital role in the integration of wind power into the electrical grid. Variable-speed wind turbine generator systems have a considerable interest of application for grid connection at constant frequency. In this paper, comprehensive simulation studies are carried out with three power converter topologies: matrix, two-level and multilevel. A fractional-order control strategy is studied for the variable-speed operation of wind turbine generator systems. The studies are in order to compare power converter topologies and control strategies. The studies reveal that the multilevel converter and the proposed fractional-order control strategy enable an improvement in the power quality, in comparison with the other power converters using a classical integer-order control strategy. (C) 2010 Elsevier Ltd. All rights reserved.

Transient analysis of variable-speed wind turbines at wind speed disturbances and a pitch control malfunction

As wind power generation undergoes rapid growth, new technical challenges emerge: dynamic stability and power quality. The influence of wind speed disturbances and a pitch control malfunction on the quality of the energy injected into the electric grid is studied for variable-speed wind turbines with different power-electronic converter topologies. Additionally, a new control strategy is proposed for the variable-speed operation of wind turbines with permanent magnet synchronous generators. The performance of disturbance attenuation and system robustness is ascertained. Simulation results are presented and conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.