Simulation and control of a stepping motor

Open-loop operatlon of the stepping motor exploits the inherent advantages of the machine. For near optimum operation: in this mode, however, an accurate system model is required to facilitate controller design. Such a model must be comprehensive and take account of the non-linearities inherent in the system. The result is a complex formulation which can be made manageable with a computational aid. A digital simulation of a hybrid type stepping motor and its associated drive circuit is proposed. The simulation is based upon a block diagram model which includes reasonable approximations to the major non-linearities. The simulation is shown to yield accurate performance predictions. The determination of the transfer functions is based upon the consideration of the physical processes involved rather than upon direct input-outout measurements. The effects of eddy currents, saturation, hysteresis, drive circuit characteristics and non-linear torque displacement characteristics are considered and methods of determining transfer functions, which take account of these effects, are offered. The static torque displacement characteristic is considered in detail and a model is proposed which predicts static torque for any combination of phase currents and shaft position. Methods of predicting the characteristic directly from machine geometry are investigated. Drive circuit design for high efficiency operation is considered and a model of a bipolar, bilevel circuit is proposed. The transfers between stator voltage and stator current and between stator current and air gap flux are complicated by the effects of eddy currents, saturation and hysteresis. Frequency response methods, combined with average inductance measurements, are shown to yield reasonable transfer functions. The modelling procedure and subsequent digital simulation is concluded to be a powerful method of non-linear analysis.

Generic wind estimation and compensation based on residual generators and higher-order sliding mode schemes

This master thesis proposes a solution to the approach problem in case of unknown severe microburst wind shear for a fixed-wing aircraft, accounting for both longitudinal and lateral dynamics. The adaptive controller design for wind rejection is also addressed, exploiting the wind estimation provided by suitable estimators. It is able to successfully complete the final approach phase even in presence of wind shear, and at the same time aerodynamic envelope protection is retained. The adaptive controller for wind compensation has been designed by a backstepping approach and feedback linearization for time-varying systems. The wind shear components have been estimated by higher-order sliding mode schemes. At the end of this work the results are provided, an autonomous final approach in presence of microburst is discussed, performances are analyzed, and estimation of the microburst characteristics from telemetry data is examined.

NIR-spectroscopy for bioprocess monitoring & control

The Ingold port adaption of a free beam NIR spectrometer is tailored for optimal bioprocess monitoring and control. The device shows an excellent signal to noise ratio dedicated to a large free aperture and therefore a large sample volume. This can be seen particularly in the batch trajectories which show a high reproducibility. The robust and compact design withstands rough process environments as well as SIP/CIP cycles. Robust free beam NIR process analyzers are indispensable tools within the PAT/QbD framework for realtime process monitoring and control. They enable multiparametric, non-invasive measurements of analyte concentrations and process trajectories. Free beam NIR spectrometers are an ideal tool to define golden batches and process borders in the sense of QbD. Moreover, sophisticated data analysis both quantitative and MSPC yields directly to a far better process understanding. Information can be provided online in easy to interpret graphs which allow the operator to make fast and knowledge-based decisions. This finally leads to higher stability in process operation, better performance and less failed batches.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.

Ambiente para avaliação de controladores fuzzy aplicados ao método de elevação artificial por bombeio centrífugo submerso

From their early days, Electrical Submergible Pumping (ESP) units have excelled in lifting much greater liquid rates than most of the other types of artificial lift and developed by good performance in wells with high BSW, in onshore and offshore environments. For all artificial lift system, the lifetime and frequency of interventions are of paramount importance, given the high costs of rigs and equipment, plus the losses coming from a halt in production. In search of a better life of the system comes the need to work with the same efficiency and security within the limits of their equipment, this implies the need for periodic adjustments, monitoring and control. How is increasing the prospect of minimizing direct human actions, these adjustments should be made increasingly via automation. The automated system not only provides a longer life, but also greater control over the production of the well. The controller is the brain of most automation systems, it is inserted the logic and strategies in the work process in order to get you to work efficiently. So great is the importance of controlling for any automation system is expected that, with better understanding of ESP system and the development of research, many controllers will be proposed for this method of artificial lift. Once a controller is proposed, it must be tested and validated before they take it as efficient and functional. The use of a producing well or a test well could favor the completion of testing, but with the serious risk that flaws in the design of the controller were to cause damage to oil well equipment, many of them expensive. Given this reality, the main objective of the present work is to present an environment for evaluation of fuzzy controllers for wells equipped with ESP system, using a computer simulator representing a virtual oil well, a software design fuzzy controllers and a PLC. The use of the proposed environment will enable a reduction in time required for testing and adjustments to the controller and evaluated a rapid diagnosis of their efficiency and effectiveness. The control algorithms are implemented in both high-level language, through the controller design software, such as specific language for programming PLCs, Ladder Diagram language.

Robust model predictive controller with output feedback and target tracking

A model predictive controller (MPC) is proposed, which is robustly stable for some classes of model uncertainty and to unknown disturbances. It is considered as the case of open-loop stable systems, where only the inputs and controlled outputs are measured. It is assumed that the controller will work in a scenario where target tracking is also required. Here, it is extended to the nominal infinite horizon MPC with output feedback. The method considers an extended cost function that can be made globally convergent for any finite input horizon considered for the uncertain system. The method is based on the explicit inclusion of cost contracting constraints in the control problem. The controller considers the output feedback case through a non-minimal state-space model that is built using past output measurements and past input increments. The application of the robust output feedback MPC is illustrated through the simulation of a low-order multivariable system.

Design and Comparison оf Mixed Hinf/H2 Controller fоr АMB System

This master’s thesis is focused on the active magnetic bearings control, specifically the robust control. As carrying out of such kind of control used mixed H2/Hinf controller. So the goal of this work is to design it using Robust Control Toolbox™ in MATLAB and compare it performance and robustness with Hinf robust controller characteristics. But only one degree-of-freedom controller considered.

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

Robust control of underactuated wheeled mobile manipulators using GPI disturbance observers

This article describes the design of a linear observer–linear controller-based robust output feedback scheme for output reference trajectory tracking tasks in the case of nonlinear, multivariable, nonholonomic underactuated mobile manipulators. The proposed linear feedback scheme is based on the use of a classical linear feedback controller and suitably extended, high-gain, linear Generalized Proportional Integral (GPI) observers, thus aiding the linear feedback controllers to provide an accurate simultaneous estimation of each flat output associated phase variables and of the exogenous and perturbation inputs. This information is used in the proposed feedback controller in (a) approximate, yet close, cancelations, as lumped unstructured time-varying terms, of the influence of the highly coupled nonlinearities, and (b) the devising of proper linear output feedback control laws based on the approximate estimates of the string of phase variables associated with the flat outputs simultaneously provided by the disturbance observers. Simulations reveal the effectiveness of the proposed approach.

Robust STATCOM control for the stabilisation of fixed-speed wind turbines during low voltages

This paper presents a robust voltage control scheme for fixed-speed wind generators using a static synchronous compensator (STATCOM) controller. To enable a linear and robust control framework with structured uncertainty, the overall system is represented by a linear part plus a nonlinear part that covers an operating range of interest required to ensure stability during severe low voltages. The proposed methodology is flexible and readily applicable to larger wind farms of different configurations. The performance of the control strategy is demonstrated on a two area test system. Large disturbance simulations demonstrate that the proposed controller enhances voltage stability as well as transient stability of induction generators during low voltage ride through (LVRT) transients and thus enhances the LVRT capability. (C) 2011 Elsevier Ltd. All rights reserved.

Automatic tuning method for the design of supplementary damping controllers for flexible alternating current transmission system devices

The design of supplementary damping controllers to mitigate the effects of electromechanical oscillations in power systems is a highly complex and time-consuming process, which requires a significant amount of knowledge from the part of the designer. In this study, the authors propose an automatic technique that takes the burden of tuning the controller parameters away from the power engineer and places it on the computer. Unlike other approaches that do the same based on robust control theories or evolutionary computing techniques, our proposed procedure uses an optimisation algorithm that works over a formulation of the classical tuning problem in terms of bilinear matrix inequalities. Using this formulation, it is possible to apply linear matrix inequality solvers to find a solution to the tuning problem via an iterative process, with the advantage that these solvers are widely available and have well-known convergence properties. The proposed algorithm is applied to tune the parameters of supplementary controllers for thyristor controlled series capacitors placed in the New England/New York benchmark test system, aiming at the improvement of the damping factor of inter-area modes, under several different operating conditions. The results of the linear analysis are validated by non-linear simulation and demonstrate the effectiveness of the proposed procedure.

Experimental investigation on adaptive robust controller designs applied to a free-floating space manipulator

This paper aims to formulate and investigate the application of various nonlinear H(infinity) control methods to a fiee-floating space manipulator subject to parametric uncertainties and external disturbances. From a tutorial perspective, a model-based approach and adaptive procedures based on linear parametrization, neural networks and fuzzy systems are covered by this work. A comparative study is conducted based on experimental implementations performed with an actual underactuated fixed-base planar manipulator which is, following the DEM concept, dynamically equivalent to a free-floating space manipulator. (C) 2011 Elsevier Ltd. All rights reserved.

An approach for reliability-based robust design optimisation of angle-ply composites

Variations of manufacturing process parameters and environmental aspects may affect the quality and performance of composite materials, which consequently affects their structural behaviour. Reliability-based design optimisation (RBDO) and robust design optimisation (RDO) searches for safe structural systems with minimal variability of response when subjected to uncertainties in material design parameters. An approach that simultaneously considers reliability and robustness is proposed in this paper. Depending on a given reliability index imposed on composite structures, a trade-off is established between the performance targets and robustness. Robustness is expressed in terms of the coefficient of variation of the constrained structural response weighted by its nominal value. The Pareto normed front is built and the nearest point to the origin is estimated as the best solution of the bi-objective optimisation problem.

A PV panel simulator based on a two quadrant DC/DC power converter with a sliding mode controller

The use of a solar photovoltaic (PV) panel simulator can be a valued tool for the design and evaluation of the several components of a photovoltaic system. This simulator is based on power electronic converter controlled in such a way that will behave as a PV panel. Thus, in this paper a PV panel simulator based on a two quadrant DC/DC power converter is proposed. This topology will allow to achieve fast responses, like suddenly changes in the irradiation and temperature. To control the power converter it will be used a fast and robust sliding mode controller. Therefore, with the proposed system I-V curve simulation of a PV panel is obtained. Experimental results from a laboratory prototype are presented in order to confirm the theoretical operation.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.