54 research outputs found

    Design and Implementation of a Furuta Pendulum Device for Benchmarking Non-Linear Control Methods

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    Furuta pendulum is an academic benchmark example for evaluating non-linear control algorithms. The main aim of this dissertation is to study this physical system, showing its dynamic model and several strategies for its control. An assortment of swing-up and upright control approaches is reported with its design and simulations. Besides, this document describes the project development which is being done at the FabLab of the Obuda University, whose objective is to design and manufacture a demonstration device that is capable to test and display various control strategies. Requirements and specications of the design, used tools and future work are described. The dissertation is structured in eight different chapters: (1) History of the Furuta pendulum, describing the origin of this system; (2) State-of-the-art in non-linear control, giving a background for the different control strategies; (3) Dynamic model of the Furuta pendulum; (4) Swing-up by energy control, based on the work of Astrom and Furuta; (5) Stabilizing local control, via full state feedback; (6) Hybrid control, which sums up the previous approaches; (7) Development project, which describes the work realized in the FabLab and (8) Conclusion, discussing the knowledge extracted from the development of this thesis

    On the Method of Interconnection and Damping Assignment Passivity-Based Control for the Stabilization of Mechanical Systems

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    Interconnection and damping assignment passivity-based control (IDA-PBC) is an excellent method to stabilize mechanical systems in the Hamiltonian formalism. In this paper, several improvements are made on the IDA-PBC method. The skew-symmetric interconnection submatrix in the conventional form of IDA-PBC is shown to have some redundancy for systems with the number of degrees of freedom greater than two, containing unnecessary components that do not contribute to the dynamics. To completely remove this redundancy, the use of quadratic gyroscopic forces is proposed in place of the skew-symmetric interconnection submatrix. Reduction of the number of matching partial differential equations in IDA-PBC and simplification of the structure of the matching partial differential equations are achieved by eliminating the gyroscopic force from the matching partial differential equations. In addition, easily verifiable criteria are provided for Lyapunov/exponential stabilizability by IDA-PBC for all linear controlled Hamiltonian systems with arbitrary degrees of underactuation and for all nonlinear controlled Hamiltonian systems with one degree of underactuation. A general design procedure for IDA-PBC is given and illustrated with examples. The duality of the new IDA-PBC method to the method of controlled Lagrangians is discussed. This paper renders the IDA-PBC method as powerful as the controlled Lagrangian method

    Polytopic Model Based Interaction Control for Soft Tissue Manipulation

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    Reliable force control is one of the key components of modern robotic teleoperation. The performance of these systems in terms of safety and stability largely depends on the controller design, as it is desired to account for various disturbing conditions, such as uncertainties of the model parameters or latency-induced problems. This work presents a polytopic qLPV model derived from a previously verified nonlinear soft tissue model, along with a model-based force control scheme that involves a tensor product polytopic state feedback controller. The derivation is based on the Tensor Product (TP) Model Transformation. The proposed force control scheme is verified and evaluated through numerical simulations. Index Terms—Soft tissue modeling, telesurgery control, Polytopic model based control, TP Model Transformation, qLPV modeling, LMI-based controller design

    Adaptive self-recurrent wavelet neural network and sliding mode controller/observer for a slider crank mechanism

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    In this paper, a novel control strategy based on an adaptive Self-Recurrent Wavelet Neural Network (SRWNN) and a sliding mode controller/observer for a slider crank mechanism is proposed. The aim is to reduce the tracking error of the linear displacement of this mechanism while following a specified trajectory. The controller design consists of two parts. The first one is a sliding mode control strategy and the second part is an SRWNN controller. This controller is trained offline first, and then the SRWNN weights are updated online by the adaptive control law. Apart from the hybrid control strategy proposed in this paper, a velocity observer is implemented to replace the use of velocity sensors. The outcomes obtained in the numerical experiment section prove that the smallest tracking error is obtained for the linear and angular displacements in comparison with other strategies found in literature due to the uncertainty and disturbance rejection properties of the sliding mode and the self-recurrent wavelet neural network controllers.Peer ReviewedPostprint (author's final draft

    A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

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    This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

    Acta Technica Jaurinensis 2021

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    Park City Lectures on Mechanics, Dynamics, and Symmetry

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    In these ve lectures, I cover selected items from the following topics: 1. Reduction theory for mechanical systems with symmetry, 2. Stability, bifurcation and underwater vehicle dynamics, 3. Systems with rolling constraints and locomotion, 4. Optimal control and stabilization of balance systems, 5. Variational integrators. Each topic itself could be expanded into several lectures, but I limited myself to what I could reasonably explain in the allotted time. The hope is that the overview is informative enough so that the reader can understand the fundamental ideas and can intelligently choose from the literature for additional details on topics of interest. Compatible with the theme of the PCI graduate school, I assume that the readers are familiar with the elements of geometric mechanics, including the basics of symplectic and Poisson geometry. The reader can find the needed background in, for example, Marsden and Ratiu [1998]

    Polytopic model based interaction control for soft tissue manipulation

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    Proc. 33. Workshop Computational Intelligence, Berlin, 23.-24.11.2023

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    Dieser Tagungsband enthält die Beiträge des 33. Workshops „Computational Intelligence“ der vom 23.11. – 24.11.2023 in Berlin stattfindet. Die Schwerpunkte sind Methoden, Anwendungen und Tools für ° Fuzzy-Systeme, ° Künstliche Neuronale Netze, ° Evolutionäre Algorithmen und ° Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen.The workshop proceedings contain the contributions of the 33rd workshop "Computational Intelligence" which will take place from 23.11. - 24.11.2023 in Berlin. The focus is on methods, applications and tools for ° Fuzzy systems, ° Artificial Neural Networks, ° Evolutionary algorithms and ° Data mining methods as well as the comparison of methods on the basis of industrial and benchmark problems
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