676 research outputs found

    Global Exponential Sampled-Data Observers for Nonlinear Systems with Delayed Measurements

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    This paper presents new results concerning the observer design for wide classes of nonlinear systems with both sampled and delayed measurements. By using a small gain approach we provide sufficient conditions, which involve both the delay and the sampling period, ensuring exponential convergence of the observer system error. The proposed observer is robust with respect to measurement errors and perturbations of the sampling schedule. Moreover, new results on the robust global exponential state predictor design problem are provided, for wide classes of nonlinear systems.Comment: 17 pages, submitted for possible publication to Systems and Control Letter

    3 sampled-data control of nonlinear systems

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    This chapter provides some of the main ideas resulting from recent developments in sampled-data control of nonlinear systems. We have tried to bring the basic parts of the new developments within the comfortable grasp of graduate students. Instead of presenting the more general results that are available in the literature, we opted to present their less general versions that are easier to understand and whose proofs are easier to follow. We note that some of the proofs we present have not appeared in the literature in this simplified form. Hence, we believe that this chapter will serve as an important reference for students and researchers that are willing to learn about this area of research

    Event-sampled direct adaptive neural network control of uncertain strict-feedback system with application to quadrotor unmanned aerial vehicle

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    Neural networks (NNs) are utilized in the backstepping approach to design a control input by approximating unknown dynamics of the strict-feedback nonlinear system with event-sampled inputs. The system state vector is assumed to be unknown and an observer is used to estimate the state vector. By using the estimated state vector and backstepping design approach, an event-sampled controller is introduced. As part of the controller design, first, input-to-state-like stability (ISS) for a continuously sampled controller that has been injected with bounded measurement errors is demonstrated and, subsequently, an event-execution control law is derived such that the measurement errors are guaranteed to remain bounded. Lyapunov theory is used to demonstrate that the tracking errors, the observer estimation errors, and the NN weight estimation errors for each NN are locally uniformly ultimately bounded (UUB) in the presence bounded disturbances, NN reconstruction errors, as well as errors introduced by event-sampling. Simulation results are provided to illustrate the effectiveness of the proposed controllers. Subsequently, the output-feedback neural network (NN) controller that was presented above is considered for an underactuated quadrotor UAV application. The flexibility for the control of a quadrotor UAV is extended by incorporating notions of event-sampling and by designing an appropriate event-execution law. First, the continuously sampled controller is considered in the presence of bounded measurement errors and it is shown that the system generates a local ISS-like Lyapunov function. Next, by designing an appropriate event-execution law, the measurement errors that result from event-sampling are shown to be bounded for all time. Finally, the effectiveness of the proposed event-sampled controller is demonstrated with simulation results --Abstract, page iv

    Regelungstheorie

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    The workshop “Regelungstheorie” (control theory) covered a broad variety of topics that were either concerned with fundamental mathematical aspects of control or with its strong impact in various fields of engineering

    Active actuator fault-tolerant control of a wind turbine benchmark model

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    This paper describes the design of an active fault-tolerant control scheme that is applied to the actuator of a wind turbine benchmark. The methodology is based on adaptive filters obtained via the nonlinear geometric approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the wind turbine system. The controller accommodation scheme exploits the on-line estimate of the actuator fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the mapping to the power conversion ratio from tip-speed ratio and blade pitch angles. This mapping represents the aerodynamic uncertainty, and usually is not known in analytical form, but in general represented by approximated two-dimensional maps (i.e. look-up tables). Therefore, this paper suggests a scheme to estimate this power conversion ratio in an analytical form by means of a two-dimensional polynomial, which is subsequently used for designing the active fault-tolerant control scheme. The wind turbine power generating unit of a grid is considered as a benchmark to show the design procedure, including the aspects of the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive simulations of the benchmark process are practical tools for assessing experimentally the features of the developed actuator fault-tolerant control scheme, in the presence of modelling and measurement errors. Comparisons with different fault-tolerant schemes serve to highlight the advantages and drawbacks of the proposed methodology
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