98 research outputs found

    Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

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    New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

    Disturbance Feedback Control for Industrial Systems:Practical Design with Robustness

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    Sustainable aviation electrification: a comprehensive review of electric propulsion system architectures, energy management, and control

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    The civil aviation sector plays an increasingly significant role in transportation sustainability in the environmental, economic, and social dimensions. Driven by the concerns of sustainability in the aviation sector, more electrified aircraft propulsion technologies have emerged and form a very promising approach to future sustainable and decarbonized aviation. This review paper aims to provide a comprehensive and broad-scope survey of the recent progress and development trends in sustainable aviation electrification. Firstly, the architectures of electrified aircraft propulsion are presented with a detailed analysis of the benefits, challenges, and studies/applications to date. Then, the challenges and technical barriers of electrified aircraft propulsion control system design are discussed, followed by a summary of the control methods frequently used in aircraft propulsion systems. Next, the mainstream energy management strategies are investigated and further utilized to minimize the block fuel burn, emissions, and economic cost. Finally, an overview of the development trends of aviation electrification is provided

    Facilitating the transition to an inverter dominated power system : experimental evaluation of a non-intrusive add-on predictive controller

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    The transition to an inverter-dominated power system is expected with the large-scale integration of distributed energy resources (DER). To improve the dynamic response of DERs already installed within such a system, a non-intrusive add-on controller referred to as SPAACE (set point automatic adjustment with correction enabled), has been proposed in the literature. Extensive simulation-based analysis and supporting mathematical foundations have helped establish its theoretical prevalence. This paper establishes the practical real-world relevance of SPAACE via a rigorous performance evaluation utilizing a high fidelity hardware-in-the-loop systems test bed. A comprehensive methodological approach to the evaluation with several practical measures has been undertaken and the performance of SPAACE subject to representative scenarios assessed. With the evaluation undertaken, the fundamental hypothesis of SPAACE for real-world applications has been proven, i.e., improvements in dynamic performance can be achieved without access to the internal controller. Furthermore, based on the quantitative analysis, observations, and recommendations are reported. These provide guidance for future potential users of the approach in their efforts to accelerate the transition to an inverter-dominated power system

    Optimal Control of Unknown Nonlinear System From Inputoutput Data

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    Optimal control designers usually require a plant model to design a controller. The problem is the controller\u27s performance heavily depends on the accuracy of the plant model. However, in many situations, it is very time-consuming to implement the system identification procedure and an accurate structure of a plant model is very difficult to obtain. On the other hand, neuro-fuzzy models with product inference engine, singleton fuzzifier, center average defuzzifier, and Gaussian membership functions can be easily trained by many well-established learning algorithms based on given input-output data pairs. Therefore, this kind of model is used in the current optimal controller design. Two approaches of designing optimal controllers of unknown nonlinear systems based on neuro-fuzzy models are presented in the thesis. The first approach first utilizes neuro-fuzzy models to approximate the unknown nonlinear systems, and then the feasible-direction algorithm is used to achieve the numerical solution of the Euler-Lagrange equations of the formulated optimal control problem. This algorithm uses the steepest descent to find the search direction and then apply a one-dimensional search routine to find the best step length. Finally several nonlinear optimal control problems are simulated and the results show that the performance of the proposed approach is quite similar to that of optimal control to the system represented by an explicit mathematical model. However, due to the limitation of the feasible-direction algorithm, this method cannot be applied to highly nonlinear and dimensional plants. Therefore, another approach that can overcome these drawbacks is proposed. This method utilizes Takagi-Sugeno (TS) fuzzy models to design the optimal controller. TS fuzzy models are first derived from the direct linearization of the neuro-fuzzy models, which is close to the local linearization of the nonlinear dynamic systems. The operating points are chosen so that the TS fuzzy model is a good approximation of the neuro-fuzzy model. Based on the TS fuzzy model, the optimal control is implemented for a nonlinear two-link flexible robot and a rigid asymmetric spacecraft, thus providing the possibility of implementing the well-established optimal control method on unknown nonlinear dynamic systems

    Advances in PID Control

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    Since the foundation and up to the current state-of-the-art in control engineering, the problems of PID control steadily attract great attention of numerous researchers and remain inexhaustible source of new ideas for process of control system design and industrial applications. PID control effectiveness is usually caused by the nature of dynamical processes, conditioned that the majority of the industrial dynamical processes are well described by simple dynamic model of the first or second order. The efficacy of PID controllers vastly falls in case of complicated dynamics, nonlinearities, and varying parameters of the plant. This gives a pulse to further researches in the field of PID control. Consequently, the problems of advanced PID control system design methodologies, rules of adaptive PID control, self-tuning procedures, and particularly robustness and transient performance for nonlinear systems, still remain as the areas of the lively interests for many scientists and researchers at the present time. The recent research results presented in this book provide new ideas for improved performance of PID control applications

    On the Robust Control of DC-DC Converters: Application to a Hybrid Power Generation System

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    International audienceIn this paper a complete robust control synthesis is performed for a hybrid power generation structure composed by a Fuel Cell and a Supercapacitor. The control strategies are applied to the DC-DC boost power converters associated to each power source. Multivariable PI control with H∞ performance, H∞ full and reduced order controllers are designed and compared. The multivariable PI controller is designed through an optimization procedure based on solving some Linear Matrix Inequalities. A μ-analysis and frequency/time response performances results shows the advantages of the different proposed control strategies

    Modelling and control of a two-link flexible manipulator using finite element modal analysis

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    This thesis focuses on Finite Element (FE) modeling and robust control of a two-link flexible manipulator based on a high resolution FE model and the system vibration modes. A new FE model is derived using Euler-Bernoulli beam elements, and the model is validated using commercial software Abaqus CAE. The frequency and time domain analysis reveal that the response of the FE model substantially varies with changing the number of elements, unless a high number of elements (100 elements in this work) is used. The gap between the complexity of the high order FE model capable of predicting dynamics of the multibody system, and suitability of the model for controller design is bridged by designing control schemes based on the reduced order models obtained using modal truncation/H8 techniques. Two reduced order multi-input multi-output modal control algorithms composed of a robust feedback controller along with a feed-forward compensator are designed. The first controller, Inversion-based Two Mode Controller (ITMC), is designed using a mixed-sensitivity H8 synthesis and a modal inversion-based compensator. The second controller, Shaping Two-Mode Controller (STMC), is designed with H8 loopshaping using the modal characteristics of the system. Stability robustness against unmodelled dynamics due to the model reduction is shown using the small gain theorem. Performance of the feedback controllers are compared with Linear Quadratic Gaussian designs and are shown to have better tracking characteristics. Effectiveness of the control schemes is shown by simulation of rest-to-rest maneuver of the manipulator to a set of desired points in the joint space. The ITMC is shown to have more precise tracking performance, while STMC has higher control over vibration of the tip, at the expense of more tracking errors
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