621,300 research outputs found

    Autonomous vehicle control using a kinematic Lyapunov-based technique with LQR-LMI tuning

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    © . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/This paper presents the control of an autonomous vehicle using a Lyapunov-based technique with a LQR-LMI tuning. Using the kinematic model of the vehicle, a non-linear control strategy based on Lyapunov theory is proposed for solving the control problem of autonomous guidance. To optimally adjust the parameters of the Lyapunov controller, the closed loop system is reformulated in a linear parameter varying (LPV) form. Then, an optimization algorithm that solves the LQR-LMI problem is used to determine the controller parameters. Furthermore, the tuning process is complemented by adding a pole placement constraint that guarantees that the maximum achievable performance of the kinematic loop could be achieved by the dynamic loop. The obtained controller jointly with a trajectory generation module are in charge of the autonomous vehicle guidance. Finally, the paper illustrates the performance of the autonomous guidance system in a virtual reality environment (SYNTHIA) and in a real scenario achieving the proposed goal: to move autonomously from a starting point to a final point in a comfortable way.Peer ReviewedPostprint (author's final draft

    Numerical Methods for Scenario Tree Nonlinear Model Predictive Control

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    In this thesis we propose new methods in the field of numerical mathematics and stochastics for a model-based optimization method to control dynamical systems under uncertainty. In model-based control the model-plant mismatch is often large and unforeseen external influences on the dynamics must be taken into account. Therefore we extend the dynamical system by a stochastic component and approximate it by scenario trees. The combination of Nonlinear Model Predictive Control (NMPC) and the scenario tree approach to robustify with respect to the uncertainty is of growing interest. In engineering practice scenario tree NMPC yields a beneficial balance of the conservatism introduced by the robustification with respect to the uncertainty and the controller performance. However, there is a high numerical effort to solve the occuring optimization problems, which heavily depends on the design of the scenario tree used to approximate the uncertainty. A big challenge is then to control the system in real-time. The contribution of this work to the field of numerical optimization is a structure exploiting method for the large-scale optimization problems based on dual decomposition that yields smaller subproblems. They can be solved in a massively parallel fashion and additionally their discretization structure can be exploited numerically. Furthermore, this thesis presents novel methods to generate suitable scenario trees to approximate the uncertainty. Our scenario tree generation based on quadrature rules for sparse grids allows for scenario tree NMPC in high-dimensional uncertainty spaces with approximation properties of the quadrature rules. A further novel approach of this thesis to generate scenario trees is based on the interpretation of the underlying stochastic process as a Markov chain. Under the Markovian assumption we provide guarantees for the scenario tree approximation of the uncertainty. Finally, we present numerical results for scenario tree NMPC. We consider dynamical systems from the chemical industry and demonstrate that the methods developed in this thesis solve optimization problems with large scenario trees in real-time

    Control-Theoretical Perspective in Feedback-Based Systems Testing

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    Self-Adaptive Systems (SAS) and Cyber-Physical Systems (CPS) have received significant attention in recent computer engineering research. This is due to their ability to improve the level of autonomy of engineering artefacts. In both cases, this autonomy increase is achieved through feedback. Feedback is the iteration of sens- ing and actuation to respectively acquire knowledge about the current state of said artefacts and steer them toward a desired state or behaviour. In this thesis we dis- cuss the challenges that the introduction of feedback poses on the verification and validation process for such systems, more specifically, on their testing. We highlight three types of new challenges with respect to traditional software testing: alteration of testing input and output definition, and intertwining of components with different nature. Said challenges affect the ways we can define different elements of the test- ing process: coverage criteria, testing set-ups, test-case generation strategies, and oracles in the testing process. This thesis consists of a collection of three papers and contributes to the definition of each of the mentioned testing elements. In terms of coverage criteria for SAS, Paper I proposes the casting of the testing problem, to a semi-infinite optimisation problem. This allows to leverage the Scenario Theory from the field of robust control, and provide a worst-case probabilistic bound on a given performance metric of the system under test. For what concerns the definition of testing set-ups for control-based CPS, Paper II investigates the implications of the use of different abstractions (i.e., the use of implemented or emulated compo- nents) on the significance of the testing. The paper provides evidence that confutes the common assumption present in previous literature on the existence of a hierar- chy among commonly used testing set-ups. Finally, regarding the test-case gener- ation and oracle definition, Paper III defines the problem of stress testing control- based CPS software. We contribute to the generation and identification of stress test cases for such software by proposing a novel test case parametrisation. Leveraging the proposed parametrisation we define metamorphic relations on the expected be- haviour of the system under test. We use said relations for the development of stress testing approach and sanity checks on the testing results

    The Role of Inverter-based Generation in Future Energy Systems: An Oriented Decentralized Strategy for Reactive Power Sharing in Islanded AC Microgrids and a Techno-Economic Approach to Inertia Requirements Assessment of the Italian Transmission Network

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    One of the most impacting changes in the electricity energy scenario of the latest decades is the extensive increase of Distributed Energy Resources (DER) including Electrical Storage Systems (EES), fuel cells and Renewable Energy Sources (RES), such as Photovoltaic (PV) and Wind Turbines (WT). The integration of a rapidly increasing share of inverter-based generation poses relevant challenges in terms of frequency and voltage control both in Islanded Microgrids (MG) and traditional transmission networks. For the sake of complementarity, the thesis focuses on reactive power and voltage regulation in MG and frequency instability problems in a future Italian transmission network. In MG with converter-based energy production, one of the main problems is the proper reactive power sharing among DER and related voltage regulation. In this concern the most used approach is based on the conventional droop control; however, it presents some relevant drawbacks. In SECTION A an Advanced Droop Control strategy (ADC) and an Advanced Boost Control strategy (ABC) are proposed, to approach primary voltage control and reactive power sharing among Grid-Supporting inverters in islanded MG. The strategies are presented defining their control laws and the control schemes together with the relevant stability analysis. Then, an analytical procedure is developed for each control methods to set proper control parameters. Next, a comparison between the new strategies and droop conventional control is performed with simulations on a common benchmark MG, in order to show that new strategies, according to their specific control logics, are able to guarantee improved performance in terms of the combined regulation of voltage and reactive power. Considering the traditional electric system, one of the main consequences of the increasing penetration of RES is, besides of the decrease of the system short-circuit power, the reduction of the electric system inertia: this could lead to frequency instability problems in case of severe perturbations, especially for what concerns the Rate of Change of Frequency (RoCoF)and the frequency nadir. In SECTION B, the thesis provides a technical-economic methodology for the estimation of the amount of additional inertia that will be needed in the Italian Transmission Network in a prospective 2030 scenario, in order to limit the RoCoF within sustainable values. Moreover, the algorithm optimally commits synthetic inertia contribution from RES and Battery Energy Storage Systems (BESS) and installation of Synchronous Compensators (SC) among the Italian market areas. The method is designed to be sufficiently simple to process a relevant number of working scenarios in order to exploit the relevant quantity of information owned by the TSO. Results have shown to be highly accurate as outline by comparison with detailed time domain simulations

    Operating market based regulation service using software agents compliant with NERC\u27s control performance standards

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    With the changing scenario for procurement of energy it becomes necessary to understand the process of obtaining energy from a diverse set of suppliers capable of providing substantial amounts of electric power at competitive prices. Sufficient insight has been gained in the energy brokerage system design and planning owing to experiences in the recently established markets especially the California market. It becomes contextual to analyze and understand the procurement of ancillary services, which are generally bundled as part of the wholesale energy supply chain, using a similarly competitive environment having a number of players that provide electric power for such services.;The objectives of this thesis are: (1) to provide a simulation package for conducting competitive auctions using software agents for the regulation service auction market, and (2) to demonstrate the compliance of a power system, employing Automatic Generation Control with parameters obtained from such a market, with North American Electric Reliability Council\u27s performance standards. The package employs a flexible and extensible Java-based agent development environment, MADKIT, to simulate the auctions for regulation service, and MATLAB/SIMULINK models with a fuzzy controller to simulate the power system. The framework is tested using a sample three-area power system, where the parameters for regulation service in the second area are obtained from a competitive auction market. A bidding strategy based on fuzzy logic is also designed and tested for ensuring good profit for a bidding supplier in the auctions

    The viability of a thermoelectric fuel conditioning system for a diesel engine utilizing biodiesel

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    Certain internal combustion engines, which run on hydrocarbon fuels, experience difficulty upon engine start-up in extreme cold weather. As ambient temperature decreases below the fuel cloud point and beyond, paraffin form in the fuel and eventually clog the fuel filter causing the engine to fail to start. This problem becomes more pronounced when the engine in question is a Diesel and the fuel utilized is biodiesel. As an alternative fuel source, biodiesel has many advantages; however, its cold weather performance is worse than even conventional diesel fuel. As biodiesel becomes more integrated into the world’s energy usage scenario, one of the systems within a Diesel engine that requires further investigation is its fuel conditioning system. This thesis describes research aimed at the development of a fuel conditioning system that utilizes several emerging technologies while decreasing the amount of electrical energy required for operation. The system utilizes a eutectic - thermoelectric (E-TE) combination which consists of a eutectic compound based latent heat storage device with adjacent thermoelectric elements to transfer waste heat stored in the eutectic reservoir into the fuel filter, thus diminishing the amount of electrical energy typically required for the fuel conditioning process. Simulations of the E-TE system are conducted while operating within three different modes (start-up, heat storage, and electrical energy generation) depending on fuel and ambient temperature conditions, while a supervisory controller distinguishes between desired operational status. The research activities and findings reported contained herein include development of E-TE system models which each consist of several components. The first of which is a set of control laws, implemented in Simulink, which control system performance using various temperature related variables. The second component is a supervisory control law, implemented in Matlab®, which controls the switching between various modes of operation. With system model developed, the viability of the system is examined

    An optimal allocation of UPFC and transient stability improvement of an electrical power system: IEEE-30 buses

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    Recently, the expansion process of electrical networks has become crucial with the development of electrical systems. One of the active solutions to progress the performance of an electrical system is the usage of flexible AC transmission system (FACTS). As a new generation of telecommunications and power electronics technology, FACTS has provided a new viewpoint to increase the bearing capacity, better control the grid, and reduce costs. The unified power flow controller had a multi-purpose unit that could command the scenario of providing or consuming the power components and maintaining the bus voltage. The study's novelty resided in presenting a modified particle swarm optimization algorithm-based software system and applied a Newton-Raphson load flow solution to get the best solutions for optimal allocation of unified power flow controllers (UPFC). This study has focused on the functions of the UPFC electrical system with corresponding effects on transient stability. MATLAB software (Simulink/code) and excel sheet were performed on IEEE 30 buses as a case study. It has been shown the effectiveness of UPFC with fast response and autonomous command on the flow of power components. The dynamic response for stability improvement for some network buses had been verified to ensure the robustness of UPFC during a sudden disturbance in electrical load. The case study results illustrate that the number of UPFC increased with load increased by (14% and 21%)

    Power management of islanded Self-Excited Induction Generator reinforced by energy storage systems

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    Self-Excited Induction Generators (SEIGs), e.g., Small-Scale Embedded wind generation, are increasingly used in electricity distribution networks. The operational stability of stand-alone SEIG is constrained by the local load conditions: stability can be achieved by maintaining the load’s active and reactive power at optimal values. Changes in power demand are dependent on customers’ requirements, and any deviation from the pre-calculated optimum setting will affect a machine’s operating voltage and frequency. This paper presents an investigation of the operation of the SEIG in islanding mode of operation under different load conditions, with the aid of batteries as an energy storage source. In this research a current-controlled voltage-source converter is proposed to regulate the power exchange between a direct current (DC) energy storage source and an alternating current (AC) grid, the converter’s controller is driven by any variation between machine capability and load demand. In order to prolong the system stability when the battery reaches its operation constraints, it is recommended that an ancillary generator and a dummy local load be embedded in the system. The results show the robustness and operability of the proposed system in the islanding mode of the SEIG under different load conditions
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