263 research outputs found

    Robust Operation and Control Synthesis of Autonomous Mobile Rack Vehicle in the Smart Warehouse

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    Nowadays, with the development of science and technology, to manage the inventory in the warehouse more efficiency, so the warehouse must have the stability and good operation chain such as receive and transfer the product to customer, storage the inventory, manage the location, making the barcode...in that operation chain, storage the inventory in the warehouse is most important thing that we must consider. In addition, to reduce costs for larger warehouse or expand the floor space of the small warehouse, it is impossible to implement this with a traditional warehouse. The warehouse is called the traditional warehouse when it uses the fixed rack. To build this type of warehouse, the space for storage must be very large. However, the cost for renting or buying the large warehouse is too expensive, so to reduce cost and build the flexible warehouse which can store the huge quantity of product within limited area, then the smart warehouse is necessary to consider. The smart warehouse system with autonomous mobile rack vehicles (MRV) increases the space utilization by providing only a few open aisles at a time for accessing the racks with minimal intervention. It is always necessary to take into account the mobile-rack vehicles (or autonomous logistics vehicles). This thesis deals with designing the robust controller for maintaining safe spacing with collision avoidance and lateral movement synchronization in the fully automated warehouse. The compact MRV dynamics are presented for the interconnected string of MRV with communication delay. Next, the string stability with safe working space of the MRV has been described for guaranteeing complete autonomous logistics in the extremely cold environment without rail rack. In addition, the controller order has been significantly reduced to the low-order system without serious performance degradation. Finally, this control method addresses the control robustness as well as the performances of MRV against unavoidable uncertainties, disturbances, and noises for warehouse automation.Contents List of Tables vii List of Figures viii Chapter 1. Introduction 1 1.1 Mobile rack vehicle 2 1.2 Leader and following vehicle 5 1.2.1 Cruise control 5 1.2.2 Adaptive cruise control 6 1.2.3 String stability of longitudinal vehicle platoon 10 1.2.4 String stability of lateral vehicle platoon 15 1.3 Problem definition 20 1.4 Purpose and aim 21 1.5 Contribution 22 Chapter 2. Robust control synthesis 23 2.1 Introduction 23 2.2 Uncertainty modeling 23 2.2.1 Unstructured uncertainties 24 2.2.2 Parametric uncertainties 25 2.2.3 Structured uncertainties 26 2.2.4 Linear fractional transformation 26 2.2.5 Coprime factor uncertainty 27 2.3 Stability criterion 31 2.3.1 Small gain theorem 31 2.3.2 Structured singular value synthesis brief definition 33 2.4 Robustness analysis and controller design 34 2.4.1 Forming generalized plant and structure 34 2.4.2 Robustness analysis 37 2.5 Robust controller using loop shaping design 39 2.5.1 Stability robustness for a coprime factor plant description 41 2.6 Reduced controller 44 2.6.1 Truncation 45 2.6.2 Residualization 46 2.6.3 Balanced realization 47 2.6.4 Optimal Hankel norm approximation 48 Chapter 3. Dynamical model of mobile rack vehicle. 53 3.1 Dynamical model of longitudinal mobile rack vehicle 53 3.2 Dynamical model of lateral mobile rack vehicle 56 3.1.1 Kinematics and dynamics of mobile rack vehicles 56 3.1.2 Lateral vehicle model with nominal value 62 Chapter 4. Controller design for mobile rack vehicle 65 4.1 Robust controller synthesis for longitudinal of mobile rack vehicles 65 4.2 Robust controller synthesis for lateral of mobile rack vehicles 73 4.2.1 Lateral vehicle model with uncertainty description 74 4.2.2 Controller design 78 4.2.3 Robust performance problem 82 4.3 String stability of connected mobile rack vehicle 85 4.4 Lower order control synthesis 87 Chapter 5. Numerical simulation and discussion 92 5.1 Mobile rack longitudinal control simulation and discussion 92 5.2 Mobile rack lateral control simulation and discussion 99 Chapter 6. Conclusion 110 Reference 112Docto

    Optimised configuration of sensing elements for control and fault tolerance applied to an electro-magnetic suspension system

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    New technological advances and the requirements to increasingly abide by new safety laws in engineering design projects highly affects industrial products in areas such as automotive, aerospace and railway industries. The necessity arises to design reduced-cost hi-tech products with minimal complexity, optimal performance, effective parameter robustness properties, and high reliability with fault tolerance. In this context the control system design plays an important role and the impact is crucial relative to the level of cost efficiency of a product. Measurement of required information for the operation of the design control system in any product is a vital issue, and in such cases a number of sensors can be available to select from in order to achieve the desired system properties. However, for a complex engineering system a manual procedure to select the best sensor set subject to the desired system properties can be very complicated, time consuming or even impossible to achieve. This is more evident in the case of large number of sensors and the requirement to comply with optimum performance. The thesis describes a comprehensive study of sensor selection for control and fault tolerance with the particular application of an ElectroMagnetic Levitation system (being an unstable, nonlinear, safety-critical system with non-trivial control performance requirements). The particular aim of the presented work is to identify effective sensor selection frameworks subject to given system properties for controlling (with a level of fault tolerance) the MagLev suspension system. A particular objective of the work is to identify the minimum possible sensors that can be used to cover multiple sensor faults, while maintaining optimum performance with the remaining sensors. The tools employed combine modern control strategies and multiobjective constraint optimisation (for tuning purposes) methods. An important part of the work is the design and construction of a 25kg MagLev suspension to be used for experimental verification of the proposed sensor selection frameworks

    Development of Robust Control Techniques towards Damage Identification

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    Robust control techniques have enabled engineers to create uncertain models which are able to describe any differences between the model and experimental system with uncertainties defined as a combination of exogenous inputs and plant perturbations. Subsequently, robust model validation techniques arose to provide a guarantee that the uncertain model is able to recreate all observed experimental data. As a result, the complete model set is robust to any model inaccuracies or external noise. At the same time, the technique of model-based identification was developed in the robust control framework to identify the dynamics resulting from unmodeled or under-modeled components in mechanical systems. The approach controls the nominal model in order to minimize the error between its response and that of the experimentally identified system. The resulting controller estimates the difference in dynamics between the model and actual system, also known as the unmodeled dynamics. In this work, a damage identification technique is developed which combines model validation and model-based identification for robust control relevant structural health monitoring. The method will both detect the presence of damage and identify the local change in dynamics due to the damage in a robust control framework. As a result, the damage detection will be robust to mismodeling and noise. Additionally, the identified damage dynamics will be defined with an uncertainty bound which will serve the dual purpose of a definition for robust control and a quality estimation of the nominal damage dynamics. The new technique is demonstrated experimentally on a rotordynamic test rig. First, feasibility of the method is verified by the identification of a fully-open seeded crack in a non-rotating shaft. Finally, the precision of the method is demonstrated through identification of a breathing crack in a rotating shaft

    Development of Robust Control Techniques towards Damage Identification

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    Robust control techniques have enabled engineers to create uncertain models which are able to describe any differences between the model and experimental system with uncertainties defined as a combination of exogenous inputs and plant perturbations. Subsequently, robust model validation techniques arose to provide a guarantee that the uncertain model is able to recreate all observed experimental data. As a result, the complete model set is robust to any model inaccuracies or external noise. At the same time, the technique of model-based identification was developed in the robust control framework to identify the dynamics resulting from unmodeled or under-modeled components in mechanical systems. The approach controls the nominal model in order to minimize the error between its response and that of the experimentally identified system. The resulting controller estimates the difference in dynamics between the model and actual system, also known as the unmodeled dynamics. In this work, a damage identification technique is developed which combines model validation and model-based identification for robust control relevant structural health monitoring. The method will both detect the presence of damage and identify the local change in dynamics due to the damage in a robust control framework. As a result, the damage detection will be robust to mismodeling and noise. Additionally, the identified damage dynamics will be defined with an uncertainty bound which will serve the dual purpose of a definition for robust control and a quality estimation of the nominal damage dynamics. The new technique is demonstrated experimentally on a rotordynamic test rig. First, feasibility of the method is verified by the identification of a fully-open seeded crack in a non-rotating shaft. Finally, the precision of the method is demonstrated through identification of a breathing crack in a rotating shaft

    Application of robust control in unmanned vehicle flight control system design

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    The robust loop-shaping control methodology is applied in the flight control system design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle. Detailed linear models for the full operational flight envelope of the air vehicle are developed. The nominal and worst-case models are determined using the v-gap metric. The effect of neglecting subsystems such as actuators and/or computation delays on modelling uncertainty is determined using the v-gap metric and shown to be significant. Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF controllers were carried out. The Hanus command signal conditioning technique is also implemented to overcome actuator saturation and windup. The robust control system is then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its capability of launch stabilization in extreme cross-wind conditions, control effectiveness in climb, and navigation precision through the prescribed 3D flight path in level cruise. Robust performance and stability of the single-point non-scheduled control law is also demonstrated throughout the full operational flight envelope the air vehicle is capable of and for all flight phases and beyond, to severe launch conditions, such as 33knots crosswind and exaggerated CG shifts. The robust TDF control law is finally compared with the classical PMC law where the actual number of variables to be manipulated manually in the design process are shown to be much less, due to the scheduling process elimination, although the size of the final controller was much higher. The robust control law performance superiority is demonstrated in the non-linear simulation for the full flight envelope and in extreme flight conditions

    Development of Robust Control Techniques towards Damage Identification

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    Robust control techniques have enabled engineers to create uncertain models which are able to describe any differences between the model and experimental system with uncertainties defined as a combination of exogenous inputs and plant perturbations. Subsequently, robust model validation techniques arose to provide a guarantee that the uncertain model is able to recreate all observed experimental data. As a result, the complete model set is robust to any model inaccuracies or external noise. At the same time, the technique of model-based identification was developed in the robust control framework to identify the dynamics resulting from unmodeled or under-modeled components in mechanical systems. The approach controls the nominal model in order to minimize the error between its response and that of the experimentally identified system. The resulting controller estimates the difference in dynamics between the model and actual system, also known as the unmodeled dynamics. In this work, a damage identification technique is developed which combines model validation and model-based identification for robust control relevant structural health monitoring. The method will both detect the presence of damage and identify the local change in dynamics due to the damage in a robust control framework. As a result, the damage detection will be robust to mismodeling and noise. Additionally, the identified damage dynamics will be defined with an uncertainty bound which will serve the dual purpose of a definition for robust control and a quality estimation of the nominal damage dynamics. The new technique is demonstrated experimentally on a rotordynamic test rig. First, feasibility of the method is verified by the identification of a fully-open seeded crack in a non-rotating shaft. Finally, the precision of the method is demonstrated through identification of a breathing crack in a rotating shaft

    Wafer Stage Motion Control:from Experiment Design to Robust Performance

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    Optimization and analysis of the current control loop of VSCs connected to uncertain grids through LCL filters

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    Premio Extraordinario de Doctorado 2011This thesis focuses on the design and analysis of the control of voltage source converters connected to the grid through LCL filters. Particularly it is centered on grids presenting uncertainty in their intrinsic dynamic parameters and their influence over the inner control loop of a grid converter: the current control. To that end, the thesis follows a three-fold discussion. Firstly, the thesis studies the grid model, its uncertain parameters and presents a proposal to recursively estimate them. The estimation is based on a recursive least-squares optimization procedure applied to the current and voltage measurements, performed in the point of common coupling, expressed in a synchronous reference frame. The synchronization and the reference frame transformation process is specially designed for the proposed system. The optimization process is complemented with an estimation evaluation block that gives a real-time measure of the estimation quality. The influence of those uncertain parameters over the stability of the current control loop of grid converters is the second topic of this thesis. For the case of linear controllers, the analysis is performed by applying the structured singular value mu theory to a parametric uncertainty model that is described in the document. The proposed method extracts safe grid parameters ranges from a previously defined controller and plant model. Special attention is payed to important practical considerations as pure real uncertainty and sampled-data systems analysis. To test the method performance and illustrate its behavior, this dissertation discusses the robustness of three particular examples: a SISO control approach, a MIMO servo-controller approach and a robust H_inf design. For the case of non-linear controllers, the thesis focuses on hysteresis controllers and presents some practical conclusions. After that analysis, the thesis deals with the complementary problem: the design of a robust controller for grid converters connected through LCL filters to grids whose parameters range between known values. As a prior stage, the thesis presents an LQ servo-controller design procedure that may be complemented with the use of state estimators. The control is faced in a synchronous reference frame and directly controls the grid injected current. Once the framework is settled, the thesis proposes a design technique based on a robust Loop-shaping H_inf design procedure complemented with the nu-gap analysis tool. The final part of this dissertation describes the experimental set-up used for testing the presented proposals. After this, a summary of experimental results and waveforms is presented

    Model-based and data-based frequency domain design of fixed structure robust controller: a polynomial optimization approach

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