792 research outputs found

    Nonlinear and sampled data control with application to power systems

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    Sampled data systems have come into practical importance for a variety of reasons. The earliest of these had primarily to do with economy of design. A more recent surge of interest was due to increase utilization of digital computers as controllers in feedback systems. This thesis contributes some control design for a class of nonlinear system exhibition linear output. The solution of several nonlinear control problems required the cancellation of some intrinsic dynamics (so-called zero dynamics) of the plant under feedback. It results that the so-dened control will ensure stability in closed-loop if and only if the dynamics to cancel are stable. What if those dynamics are unstable? Classical control strategies through inversion might solve the problem while making the closed loop system unstable. This thesis aims to introduce a solution for such a problem. The main idea behind our work is to stabilize the nonminimum phase system in continuous- time and undersampling using zero dynamics concept. The overall work in this thesis is divided into two parts. In Part I, we introduce a feedback control designs for the input-output stabilization and the Disturbance Decoupling problems of Single Input Single Output nonlinear systems. A case study is presented, to illustrate an engineering application of results. Part II illustrates the results obtained based on the Articial Intelligent Systems in power system machines. We note that even though the use of some of the AI techniques such as Fuzzy Logic and Neural Network does not require the computation of the model of the application, but it will still suer from some drawbacks especially regarding the implementation in practical applications. An alternative used approach is to use control techniques such as PID in the approximated linear model. This design is very well known to be used, but it does not take into account the non-linearity of the model. In fact, it seems that control design that is based on nonlinear control provide better performances

    Robust Nonlinear Control Strategy for Small Wind Turbines: A Case Study

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    This chapter presents a case study of robust nonlinear control strategy using nonlinear feedback control technique based on Lyapunov theory and associated with robust control laws. The proposed approach aims to enhance robustness of the wind turbine control scheme. In fact, we selected as a case study, the most used electrical generator in small-scale wind applications, the Permanent Magnet Synchronous Generator (PMSM). Indeed, the control strategy presented in this chapter allows an efficient operation of the wind turbine in the standalone operating mode, offers a nonlinear handling of the WECS(s) and guarantees maximum wind power harvesting and robustness against critical working conditions. Talking about stability, in several wind generator control schemes; a such classical PI controllers-based scheme can easily be disturbed by any uncertainty of the system parameters, thus, in this chapter, we focused on how to overcome this issue by proposing a robust control strategy based on nonlinear controller derived from the Lyapunov Theory. The chapter presents numerical simulations within Matlab/SIMULINK environment. These results proved the effectiveness and the benefits of the proposed approach

    Nonlinear optimal control for permanent magnet synchronous spherical motors

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    Purpose – Permanent magnet synchronous spherical motors can have wide use in robotics and industrial automation. They enable three-DOF omnidirectional motion of their rotor. They are suitable for several applications, such as actuation in robotics, traction in electric vehicles and use in several automation systems. Unlike conventional synchronous motors, permanent magnet synchronous spherical motors consist of a fixed inner shell, which is the stator, and a rotating outer shell, which is the rotor. Their dynamic model is multivariable and strongly nonlinear. The treatment of the associated control problem is important. Design/methodology/approach – In this paper, the multivariable dynamic model of permanent magnet synchronous spherical motors is analysed, and a nonlinear optimal (H-infinity) control method is developed for it. Differential flatness properties are proven for the spherical motors’ state-space model. Next, the motors’ state-space description undergoes approximate linearization with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. The linearization process takes place at each sampling instance around a time-varying operating point, which is defined by the present value of the motors’ state vector and by the last sampled value of the control input vector. For the approximately linearized model of the permanent magnet synchronous spherical motors, a stabilizing H-infinity feedback controller is designed. To compute the controller’s gains, an algebraic Riccati equation has to be repetitively solved at each time-step of the control algorithm. The global stability properties of the control scheme are proven through Lyapunov analysis. Finally, the performance of the nonlinear optimal control method is compared against a flatness-based control approach implemented in successive loops. Findings – Due to the nonlinear and multivariable structure of the state-space model of spherical motors, the solution of the associated nonlinear control problem is a nontrivial task. In this paper, a novel nonlinear optimal (H-infinity) control approach is proposed for the dynamic model of permanent magnet synchronous spherical motors. The method is based on approximate linearization of the motor’s state-space model with the use of first-order Taylor series expansion and the computation of the associated Jacobian matrices. Furthermore, the paper has introduced a different solution to the nonlinear control problem of the permanent magnet synchronous spherical motor, which is based on flatness-based control implemented in successive loops. Research limitations/implications – The presented control approaches do not exhibit any limitations, but on the contrary, they have specific advantages. In comparison to global linearization-based control schemes (such as Lie-algebra-based control), they do not make use of complicated changes of state variables (diffeomorphisms) and transformations of the system's state-space description. The computed control inputs are applied directly to the initial nonlinear state-space model of the permanent magnet spherical motor without the intervention of inverse transformations and thus without coming against the risk of singularities. Practical implications – The motion control problem of spherical motors is nontrivial because of the complicated nonlinear and multivariable dynamics of these electric machines. So far, there have been several attempts to apply nonlinear feedback control to permanent magnet-synchronous spherical motors. However, due to the model’s complexity, few results exist about the associated nonlinear optimal control problem. The proposed nonlinear control methods for permanent magnet synchronous spherical motors make more efficient, precise and reliable the use of such motors in robotics, electric traction and several automation systems. Social implications – The treated research topic is central for robotic and industrial automation. Permanent magnet synchronous spherical motors are suitable for several applications, such as actuation in robotics, traction in electric vehicles and use in several automation systems. The solution of the control problem for the nonlinear dynamic model of permanent magnet synchronous spherical motors has many industrial applications and therefore contributes to economic growth and development. Originality/value – The proposed nonlinear optimal control method is novel compared to past attempts to solve the optimal control problem for nonlinear dynamical systems. Unlike past approaches, in the new nonlinear optimal control method, linearization is performed around a temporary operating point, which is defined by the present value of the system's state vector and by the last sampled value of the control inputs vector and not at points that belong to the desirable trajectory (setpoints). Besides, the Riccati equation which is used for computing the feedback gains of the controller is new, and so is the global stability proof for this control method. Compared to nonlinear model predictive control, which is a popular approach for treating the optimal control problem in industry, the new nonlinear optimal (H-infinity) control scheme is of proven global stability, and the convergence of its iterative search for the optimum does not depend on initial conditions and trials with multiple sets of controller parameters. It is also noteworthy that the nonlinear optimal control method is applicable to a wider class of dynamical systems than approaches based on the solution of state dependent Riccati equations (SDRE). The SDRE approaches can be applied only to dynamical systems which can be transformed into the linear parameter varying form. Besides, the nonlinear optimal control method performs better than nonlinear optimal control schemes, which use approximation of the solution of the Hamilton–Jacobi–Bellman equation by Galerkin series expansions. Furthermore, the second control method proposed in this paper, which is flatness-based control in successive loops, is also novel and demonstrates substantial contribution to nonlinear control for robotics and industrial automation

    Phasor model of full scale converter wind turbine for small-signal stability analysis

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    A two frame feedback linearization scheme for the control of fully rated wind generating units

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    The present paper proposes an innovative control scheme for a fully rated wind generating unit equipped with a permanent magnet synchronous generator. The main objective of this control strategy is that of allowing a decoupled and dynamically performing control of active power (by the MPPT curve) and reactive power at the point of interconnection to the grid. Moreover, the control will be able to integrate frequency supporting logics, such as synthetic inertial control and active power curtailment. The control synthesis is fully detailed and validated by means of dedicated simulations in comparison with the traditional control scheme for this type of wind generators

    Cogging torque reduction in brushless motors by a nonlinear control technique

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    This work addresses the problem of mitigating the effects of the cogging torque in permanent magnet synchronous motors, particularly brushless motors, which is a main issue in precision electric drive applications. In this work, a method for mitigating the effects of the cogging torque is proposed, based on the use of a nonlinear automatic control technique known as feedback linearization that is ideal for underactuated dynamic systems. The aim of this work is to present an alternative to classic solutions based on the physical modification of the electrical machine to try to suppress the natural interaction between the permanent magnets and the teeth of the stator slots. Such modifications of electric machines are often expensive because they require customized procedures, while the proposed method does not require any modification of the electric drive. With respect to other algorithmic-based solutions for cogging torque reduction, the proposed control technique is scalable to different motor parameters, deterministic, and robust, and hence easy to use and verify for safety-critical applications. As an application case example, the work reports the reduction of the oscillations for the angular position control of a permanent magnet synchronous motor vs. classic PI (proportional-integrative) cascaded control. Moreover, the proposed algorithm is suitable to be implemented in low-cost embedded control units

    New design and comparative study via two techniques for wind energy conversion system

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    Introduction. With the advancements in the variable speed direct drive design and control of wind energy systems, the efficiency and energy capture of these systems is also increasing. As such, numerous linear controllers have also been developed, in literature, for MPPT which use the linear characteristics of the wind turbine system. The major limitation in all of those linear controllers is that they use the linearized model and they cannot deal with the nonlinear dynamics of a system. However, real systems exhibit nonlinear dynamics and a nonlinear controller is required to handle such nonlinearities in real-world systems. The novelty of the proposed work consists in the development of a robust nonlinear controller to ensure maximum power point tracking by handling nonlinearities of a system and making it robust against changing environmental conditions. Purpose. In the beginning, sliding mode control has been considered as one of the most powerful control techniques, this is due to the simplicity of its implementation and robustness compared to uncertainties of the system and external disturbances. Unfortunately, this type of controller suffers from a major disadvantage, that is, the phenomenon of chattering. Methods. So in this paper and in order to eliminate this phenomenon, a novel non-linear control algorithm based on a synergetic controller is proposed. The objective of this control is to maximize the power extraction of a variable speed wind energy conversion system compared to sliding mode control by eliminating the phenomenon of chattering and have a good power quality by fixing the power coefficient at its maximum value and the Tip Speed Ratio maintained at its optimum value. Results. The performance of the proposed nonlinear controllers has been validated in MATLAB/Simulink environment. The simulation results show the effectiveness of the proposed scheme, suppression of the chattering phenomenon and robustness of the proposed controller compared to the sliding mode control law.Вступ. З досягненнями у проектуванні та керуванні вітряними енергосистемами з регульованою швидкістю, зростають також ефективність та захоплення енергії цих систем. Так, в літературі також розроблено численні лінійні контролери для відстеження точки максимальної потужності, які використовують лінійні характеристики системи з вітряними турбінами. Основним обмеженням у всіх цих лінійних контролерах є те, що вони використовують лінеаризовану модель і не можуть мати справу з нелінійною динамікою системи. Однак реальні системи демонструють нелінійну динаміку, і для обробки таких нелінійностей у реальних системах необхідний нелінійний контролер. Новизна запропонованої роботи полягає у розробці надійного нелінійного контролера для забезпечення відстеження точки максимальної потужності шляхом обробки нелінійності системи та забезпечення її стійкості до змін умов навколишнього середовища. Мета. Спочатку управління ковзним режимом вважалося одним з найпотужніших методів управління, що пов’язано з простотою його реалізації та надійністю порівняно з невизначеністю системи та зовнішніми збуреннями. На жаль, цей тип контролера страждає від головного недоліку, а саме явища вібрування. Методи. Тому у цій роботі з метою усунення цього явища пропонується новий нелінійний алгоритм управління, заснований на синергетичному контролері. Завдання цього контролю – максимізувати відбір потужності системи перетворення енергії вітру зі змінною швидкістю порівняно із регулюванням ковзного режиму, усуваючи явище вібрування, і мати хорошу якість енергії, фіксуючи коефіцієнт потужності на його максимальному значенні та підтримуючи кінцевий коефіцієнт швидкості на його оптимальному значенні. Результати. Ефективність запропонованих нелінійних контролерів перевірена в середовищі MATLAB/Simulink. Результати моделювання показують ефективність запропонованої схеми, придушення явища вібрування та стійкість запропонованого контролера порівняно із законом управління ковзного режиму

    FLATNESS BASED CONTROL OF MICRO-HYDROKINETIC RIVER ELECTRIFICATION SYSTEM

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    Published ThesisIn areas where adequate water resource is available, hydrokinetic energy conversion systems are currently gaining recognition, as opposed to other renewable energy sources such as solar or wind energy. The operational principle of hydrokinetic energy is not similar to traditional hydropower generation that explores use of the potential energy of falling water, which has drawbacks such as the expensive construction of dams and the disturbance of aquatic ecosystems. Hence, hydrokinetic energy generates electricity by making use of underwater turbines to extract the kinetic energy of flowing water, with no construction of dams or diversions. A hydrokinetic turbine uses flowing water, which varies with climatic conditions throughout the year, to power the shaft of a generator, hence, generating an unstable energy output. The aim of this dissertation is to develop a controller that will be used to stabilize the output voltage and frequency generated in a hydrokinetic energy system. An overview of various methods used to minimize the fluctuating impacts of power generated from renewable energy sources is included in the current conducted research. Several renewable energy sources such as biomass, wind, solar, hydro and geothermal have been discussed in the literature review. Different control methods and topologies have been cited. Hence, the study elaborates on the adoptive control principles, which include the load ballast control, dummy load control, proportional integral and derivative (PID) controller system, proportional integral (PI) controller system, pulse-width modulation (PWM) control, pitch angle control, valve control, the rate of river flow at the turbine, bidirectional diffuser-augmented control and differential flatness based controller. These control operations in renewable energy power generation are mainly based on a linear control approach. In the case whereby a PI power controller system has been developed for a variable speed hydrokinetic turbine system, a DC-DC boost converter is used to keep constant DC link voltage. The input DC current is regulated to follow the optimized current reference for maximum power point operation of the turbine system. The DC link voltage is controlled to feed the current in the grid through the line side PWM inverter. The active power is regulated by q-axis current while the reactive power is regulated by d-axis current. The phase angle of utility voltage is detected using PLL (phased locked loop) in a d-q synchronous reference frame. The proposed scheme is modelled and simulated using MATLAB/ Simulink, and the results give a high quality power conversion solution for a variable speed hydrokinetic system. In the second case, whereby the differential flatness concept is applied to a controller, the idea of this concept is to generate an imaginary trajectory that will take the system from an initial condition to a desired output generating power. This control concept has the ability to resolve complex control problems such as output voltage and frequency fluctuations of renewable energy systems, while exploiting their linear properties. The results show that the generated outputs are dynamically adjusted during the voltage regulation process. The advantage of the proposed differential flatness based controller over the traditional PI control resides in the fact that decoupling is not necessary and the system is much more robust as demonstrated by the modelling and simulation studies under different operating conditions, such as changes in water flow rate
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