518 research outputs found

    Teaching, Analyzing, Designing and Interactively Simulating of Sliding Mode Control

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    This paper introduces an interactive methodology to analize, design, and simulate sliding model controllers for R2 linear systems. This paper reviews sliding mode basic concepts and design methodologies and describes an interactive tool which has been developed to support teaching in this field. The tool helps students by generating a nice graphical and interactive display of most relevant concepts. This fact can be used so that students build their own intuition about the role of different parameters in a sliding mode controller. Described application has been coded with Sysquake using an event-driven solver technique. The Sysquake allows using precise integration methods in real time and handling interactivity in a simple manner.Peer ReviewedPostprint (published version

    Model Prediction-Based Approach to Fault Tolerant Control with Applications

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    Abstract— Fault-tolerant control (FTC) is an integral component in industrial processes as it enables the system to continue robust operation under some conditions. In this paper, an FTC scheme is proposed for interconnected systems within an integrated design framework to yield a timely monitoring and detection of fault and reconfiguring the controller according to those faults. The unscented Kalman filter (UKF)-based fault detection and diagnosis system is initially run on the main plant and parameter estimation is being done for the local faults. This critical information\ud is shared through information fusion to the main system where the whole system is being decentralized using the overlapping decomposition technique. Using this parameter estimates of decentralized subsystems, a model predictive control (MPC) adjusts its parameters according to the\ud fault scenarios thereby striving to maintain the stability of the system. Experimental results on interconnected continuous time stirred tank reactors (CSTR) with recycle and quadruple tank system indicate that the proposed method is capable to correctly identify various faults, and then controlling the system under some conditions

    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

    Formal analysis of state estimation for nonlinear model predictive control

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    The main goal of this study is to carry out a closed-loop performance analysis of state estimation methods when implemented in the formulation of nonlinear model predictive control. The analysis is facilitated by two nonlinear optimal state estimation methods: augmented state EKF (ASEKF) and augmented state UKF (ASUKF) for comparison purposes. Each state estimation method is coupled to the same NMPC controller to form state estimation-based NMPC controllers, that is, to form the ASEKF-NMPC and ASUKFNMPC controllers. The resulting NMPC controllers are applied for position control of the magnetic levitation system to validate their closed-loop performances. The ASEKFNMPC and ASUKF-NMPC controllers are further applied for the angular position control of the inverted pendulum mounted on a cart system for comparative analysis. The controlled system is perturbed with different error sources: output step disturbance and 5%parametric plant-model mismatch. Output step disturbance is introduced to the system to disturb the pendulum from its upright position while the 5% mismatch is applied to the parameters of the model of the controlled system throughout the simulation. To facilitate fair analysis, Pareto front ranking method is chosen as an evaluation method whereby the cost functions are defined according to the author's preferences. The cost functions served as performance markers for analyzing performance of ASEKF and ASUKF in NMPC formulation in multidimensional space. The tunable parameters of the ASEKFNMPC and ASUKF-NMPC controllers are chosen to be the decision variables of the evaluation problem. The state estimation methods are evaluated in terms of estimation accuracy, system's response time, peak overshoot and control performance. The Level Diagrams tool is used for good visualization of the Pareto fronts to evaluate which estimator performs better in the closed-loop. Finally, the points on the Level Diagrams which provide a performance closest to the desired are selected and tested through simulation runs on the inverted pendulum on a moving cart system

    Guaranteed set-based controller design for hybrid dynamical systems

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    Index to 1984 NASA Tech Briefs, volume 9, numbers 1-4

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    Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1984 Tech B Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

    Model Identification, Updating, and Validation of an Active Magnetic Bearing High-Speed Machining Spindle for Precision Machining Operation

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    High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) are envisioned to be capable of autonomous self-identification and performance self-optimization for stable high-speed and high quality machining operation. High-speed machining requires carefully selected parameters for reliable and optimal machining performance. For this reason, the accuracy of the spindle model in terms of physical and dynamic properties is essential to substantiate confidence in its predictive aptitude for subsequent analyses.This dissertation addresses system identification, open-loop model development and updating, and closed-loop model validation. System identification was performed in situ utilizing the existing AMB hardware. A simplified, nominal open-loop rotor model was developed based on available geometrical and material information. The nominal rotor model demonstrated poor correlation when compared with open-loop system identification data. Since considerable model error was realized, the nominal rotor model was corrected by employing optimization methodology to minimize the error of resonance and antiresonance frequencies between the modeled and experimental data.Validity of the updated open-loop model was demonstrated through successful implementation of a MIMO u-controller. Since the u-controller is generated based on the spindle model, robust levitation of the real machining spindle is achieved only when the model is of high fidelity. Spindle performance characterization was carried out at the tool location through evaluations of the dynamic stiffness as well as orbits at various rotational speeds. Updated model simulations exhibited high fidelity correspondence to experimental data confirming the predictive aptitude of the updated model. Further, a case study is presented which illustrates the improved performance of the u-controller when designed with lower uncertainty of the model\u27s accurac

    Model Identification, Updating, and Validation of an Active Magnetic Bearing High-Speed Machining Spindle for Precision Machining Operation

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    High-Speed Machining (HSM) spindles equipped with Active Magnetic Bearings (AMBs) are envisioned to be capable of autonomous self-identification and performance self-optimization for stable high-speed and high quality machining operation. High-speed machining requires carefully selected parameters for reliable and optimal machining performance. For this reason, the accuracy of the spindle model in terms of physical and dynamic properties is essential to substantiate confidence in its predictive aptitude for subsequent analyses.This dissertation addresses system identification, open-loop model development and updating, and closed-loop model validation. System identification was performed in situ utilizing the existing AMB hardware. A simplified, nominal open-loop rotor model was developed based on available geometrical and material information. The nominal rotor model demonstrated poor correlation when compared with open-loop system identification data. Since considerable model error was realized, the nominal rotor model was corrected by employing optimization methodology to minimize the error of resonance and antiresonance frequencies between the modeled and experimental data.Validity of the updated open-loop model was demonstrated through successful implementation of a MIMO u-controller. Since the u-controller is generated based on the spindle model, robust levitation of the real machining spindle is achieved only when the model is of high fidelity. Spindle performance characterization was carried out at the tool location through evaluations of the dynamic stiffness as well as orbits at various rotational speeds. Updated model simulations exhibited high fidelity correspondence to experimental data confirming the predictive aptitude of the updated model. Further, a case study is presented which illustrates the improved performance of the u-controller when designed with lower uncertainty of the model\u27s accurac

    Proportional-Integral-Derivative Gain-Scheduling Control of a Magnetic Levitation System

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    The paper presents a gain-scheduling control design procedure for classical Proportional-Integral-Derivative controllers (PID-GS-C) for positioning system. The method is applied to a Magnetic Levitation System with Two Electromagnets (MLS2EM) laboratory equipment, which allows several experimental verifications of the proposed solution. The nonlinear model of MLS2EM is linearized at seven operating points. A state feedback control structure is first designed to stabilize the process. PID control and PID-GS-C structures are next designed to ensure zero steady-state control error and bumpless switching between PID controllers for the linearized models. Real-time experimental results are presented for validation.

    FLUX-PINNED DYNAMICAL SYSTEMS WITH APPLICATION TO SPACEFLIGHT

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    Technology enables space exploration and scientific discovery. At this amazing intersection of time, new software and hardware capabilities give rise to daring robotic exploration and autonomy. Close-proximity operations for spacecraft is a particularly critical portion of any robotic mission that enables many types of maneuvers, such as docking and capture, formation flying, and on-orbit assembly. These dynamic maneuvers then enable different missions, like sample return, spacecraft construction larger than a single rocket faring, and deep-space operations. Commonly, spacecraft dynamic control uses thrusters for position and attitude control, which rely on active sensing and consumable propellant. The development of other dynamic control techniques opens new capabilities and system advantages, and further offers a more diverse technological trade space for system optimization. This research comprehensively investigates the utilization of flux-pinning physics to manipulate spacecraft dynamics. Flux-pinned interfaces differ from conventional dynamic control through its passive and compliant behavior. These unique characteristics are extremely attractive for certain applications, but flux-pinned technology must mature considerably before adoption for spaceflight missions. A dynamic capture and docking maneuver in an upcoming mission concept, Mars Sample Return, motivates the technology design. This body of work as much as possible follows a progression from cradle to grave. A flux-pinning theoretical dynamics model and a system architecture are presented to specify general capabilities of such a spacecraft system. Different analyses on stability, state sensitivity, backwards reachability result from a physics-based dynamics model. An extensive literature review and basic science experiments inform a theoretical dynamics model about the incorporation of physical parameters when simulating realistic dynamics. A series of testbeds enable experimentation and precise investigation of flux-pinned interface capabilities in the context of docking and capture. The testbeds ranged from the simplest expression of dynamics, in a single degree of freedom, to a flight traceable expression, in all six degrees of freedom. Experiments from these testbeds define and characterize system level capabilities specific to flux-pinned capture. Data collected from these experiments then supports development of a predictive dynamics model of the hardware system. Various system identification methods aid in creating a dynamics model that accurately predicts the dynamics observed during experiments. Several objective metrics are considered to evaluate the model fidelity. The types of system identification methods are separated into analytical methods and numerical methods. The analytical method involves parameter estimation in a physics-based model. Numerical methods involve Taylor expansion, bag of functions, symbolic regression, and neural networks. Theoretical extensions towards verification further develops neural network approximation methods, driving at safe, real-time system identification
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