Scaling Technique

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The Experts below are selected from a list of 306 Experts worldwide ranked by ideXlab platform

Syyen Kuo - One of the best experts on this subject based on the ideXlab platform.

Tehuan Chen - One of the best experts on this subject based on the ideXlab platform.

  • computational optimal control of the saint venant pde model using the time Scaling Technique
    Asia-Pacific Journal of Chemical Engineering, 2016
    Co-Authors: Tehuan Chen
    Abstract:

    This paper proposes a new time-Scaling approach for computational–optimal control of a distributed parameter system governed by the Saint–Venant partial differential equations (PDEs). We propose the time-Scaling approach that can change a uniform time partition to a nonuniform one. We also derive the gradient formulas by using the variational method. Then, the method of lines is applied to compute the Saint–Venant PDEs after implementing the time-Scaling transformation and the associate costate PDEs. Finally, we compare the optimization results using the proposed time-Scaling approach with the one not using it. The simulation result demonstrates the effectiveness of the proposed time-Scaling method. © 2015 Curtin University of Technology and John Wiley & Sons, Ltd.

  • computational optimal control of the saint venant pde model using the time Scaling Technique
    arXiv: Systems and Control, 2015
    Co-Authors: Tehuan Chen
    Abstract:

    This paper proposes a new time-Scaling approach for computational optimal control of a distributed parameter system governed by the Saint-Venant PDEs. We propose the time-Scaling approach, which can change a uniform time partition to a nonuniform one. We also derive the gradient formulas by using the variational method. Then the method of lines (MOL) is applied to compute the Saint-Venant PDEs after implementing the time-Scaling transformation and the associate costate PDEs. Finally, we compare the optimization results using the proposed time-Scaling approach with the one not using it. The simulation result demonstrates the effectiveness of the proposed time-Scaling method.

Yijong Yeh - One of the best experts on this subject based on the ideXlab platform.

Farshad Khorrami - One of the best experts on this subject based on the ideXlab platform.

  • a high gain Scaling Technique for adaptive output feedback control of feedforward systems
    IEEE Transactions on Automatic Control, 2004
    Co-Authors: Prashanth Krishnamurthy, Farshad Khorrami
    Abstract:

    In this note, we propose an adaptive output feedback control design Technique for feedforward systems based on our recent results on dynamic high-gain Scaling Techniques for controller design for strict-feedback systems. The system is allowed to contain uncertain functions of all the states and the input as long as the uncertainties satisfy certain bounds. Unknown parameters are allowed in the bounds assumed on the uncertain functions. If the uncertain functions involve the input, then the output-dependent functions in the bounds on the uncertain functions need to be polynomially bounded. It is also shown that if the uncertain functions can be bounded by a function independent of the input, then the polynomial boundedness requirement can be relaxed. The designed controllers have a very simple structure being essentially a linear feedback with state-dependent dynamic gains and do not involve any saturations or recursive computations. The observer utilized to estimate the unmeasured states is similar to a Luenberger observer with dynamic observer gains. The Lyapunov functions are quadratic in the state estimates, the observer errors, and the parameter estimation error. The stability analysis is based on our recent results on uniform solvability of coupled state-dependent Lyapunov equations. The controller design provides strong robustness properties both with respect to uncertain parameters in the system model and additive disturbances. This robustness is the key to the output feedback controller design. Global asymptotic results are obtained.

  • A high gain multiple time-Scaling Technique for global control of nonlinear systems
    Proceedings of the 2004 American Control Conference, 2004
    Co-Authors: Prashanth Krishnamurthy, Farshad Khorrami
    Abstract:

    We consider a general high-gain Scaling Technique for global control of strict-feedback-like systems. Unlike previous results, the Scaling utilizes arbitrary powers (instead of requiring successive powers) of the high gain parameter with the powers chosen to satisfy certain inequalities depending on system nonlinearities. The Scaling induces a weak-cascading upper diagonal dominance (w-CUDD) structure on the dynamics. The analysis is based on our recent results on the w-CUDD property and uniform solvability of coupled state-dependent Lyapunov equations. The proposed Scaling provides extensions in both state-feedback and output-feedback cases. The state-feedback problem is solved for a class of systems with certain ratios of nonlinear terms being polynomially bounded. The controller has a simple form being essentially linear with state-dependent dynamic gains and does not involve recursive computations. In the output-feedback case, the Scaling Technique is applied to the design of the observer which is then coupled with a backstepping controller. The results relax the assumption in our earlier papers on cascading dominance of upper diagonal terms. However, since the required upper diagonal cascading dominance in observer and controller contexts are dual, it is not possible to use a dual high-gain observer/controller in the proposed design preventing the bounds on uncertain functions from being of the more general form in our earlier work. A topic of further research is to examine the possibility of a Scaling (perhaps utilizing more than one high gain parameter) that achieves bidirectional cascading dominance.

Pierre Tournois - One of the best experts on this subject based on the ideXlab platform.