Home About us Contact
|
Home About us Contact | ||
|
|
||
Parameter Perturbation (parameter + perturbation)
Selected AbstractsA bioenergetics model for juvenile flounder Platichthys flesusJOURNAL OF APPLIED ICHTHYOLOGY, Issue 1 2006M. Stevens Summary Despite the numerous physiological studies on flatfish and their economic and ecologic importance, only a few attempts have been made to construct a bioenergetics model for these species. Here we present the first bioenergetics model for European flounder (Platichthys flesus), using experimentally derived parameter values. We tested model performance using literature derived field-based estimates of food consumption and growth rates of an estuarine flounder population in the Ythan estuary, Scotland. The model was applied to four age-classes of flounder (age 0,3). Sensitivity of model predictions to parameter perturbation was estimated using error analysis. The fit between observed and predicted series was evaluated using three statistical methods: partitioning mean squared error, a reliability index (RI) and an index of modelling efficiency (MEF). Overall, model predictions closely tracked the observed changes of consumption and growth. The results of the different validation techniques show a high goodness-of-fit between observed and simulated values. The model clearly demonstrates the importance of temperature in determining growth of flounder in the estuary. A sex-specific estimation of the energetic costs of spawning in adult flounder and a more accurate description of the thermal history of the fish may further reduce the error in the model predictions. [source] Observer-based non-fragile control against measurement disturbances and controller perturbations for discrete systems with state delay ,ASIAN JOURNAL OF CONTROL, Issue 3 2009Xiaosheng Fang Abstract This paper investigates the observer-based non-fragile control problem for a class of discrete time delay systems with measurement disturbances and controller perturbations. A simultaneous state and disturbance estimation technique is developed by designing a state observer for a descriptor system obtained from the original system. Based on this observer, the design method of a non-fragile controller is then formulated and the controller design problem is transformed to a convex optimization problem, which can be solved by a linear matrix inequality approach. In this design, the additive and multiplicative forms of uncertainties which perturb the gains of control and observer are both considered. The resultant non-fragile observer-based controller guarantees that the closed-loop system is asymptotically stable and can tolerate measurement disturbances and a certain degree of controller parameter perturbation. A numerical example is given to illustrate the effectiveness of the proposed design method. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society [source] Adaptive L2 Disturbance Attenuation Of Hamiltonian Systems With Parametric Perturbation And Application To Power SystemsASIAN JOURNAL OF CONTROL, Issue 1 2003Tielong Shen ABSTRACT This paper deals with the problem of L2 disturbance attenuation for Hamiltonian systems. We first show that the L2 gain from the disturbance to a penalty signal may be reduced to any given level if the penalty signal is defined properly. Then, an adaptive version of the controller will be presented to compensate the parameter perturbation. When the perturbed parameters satisfy a suitable matching condition, it is easy to introduce the adaptive mechanism to the controller. Another contribution of this paper is to apply the proposed method to the excitation control problem for power systems. An adaptive L2 controller for the power system is designed using the proposed method and a simulation result with the proposed controller is given. [source] A review of the adjoint-state method for computing the gradient of a functional with geophysical applicationsGEOPHYSICAL JOURNAL INTERNATIONAL, Issue 2 2006R.-E. Plessix SUMMARY Estimating the model parameters from measured data generally consists of minimizing an error functional. A classic technique to solve a minimization problem is to successively determine the minimum of a series of linearized problems. This formulation requires the Fréchet derivatives (the Jacobian matrix), which can be expensive to compute. If the minimization is viewed as a non-linear optimization problem, only the gradient of the error functional is needed. This gradient can be computed without the Fréchet derivatives. In the 1970s, the adjoint-state method was developed to efficiently compute the gradient. It is now a well-known method in the numerical community for computing the gradient of a functional with respect to the model parameters when this functional depends on those model parameters through state variables, which are solutions of the forward problem. However, this method is less well understood in the geophysical community. The goal of this paper is to review the adjoint-state method. The idea is to define some adjoint-state variables that are solutions of a linear system. The adjoint-state variables are independent of the model parameter perturbations and in a way gather the perturbations with respect to the state variables. The adjoint-state method is efficient because only one extra linear system needs to be solved. Several applications are presented. When applied to the computation of the derivatives of the ray trajectories, the link with the propagator of the perturbed ray equation is established. [source] Nonlinear model predictive control for the polymorphic transformation of L -glutamic acid crystalsAICHE JOURNAL, Issue 10 2009Martin Wijaya Hermanto Abstract Polymorphism, a phenomenon where a substance can have more than one crystal forms, has recently become a major interest to the food, speciality chemical, and pharmaceutical industries. The different physical properties for polymorphs such as solubility, morphology, and dissolution rate may jeopardize operability or product quality, resulting in significant effort in controlling crystallization processes to ensure consistent production of the desired polymorph. Here, a nonlinear model predictive control (NMPC) strategy is developed for the polymorphic transformation of L -glutamic acid from the metastable ,-form to the stable ,-form crystals. The robustness of the proposed NMPC strategy to parameter perturbations is compared with temperature control (T-control), concentration control (C-control), and quadratic matrix control with successive linearization (SL-QDMC). Simulation studies show that T-control is the least robust, whereas C-control performs very robustly but long batch times may be required. SL-QDMC performs rather poorly even when there is no plant-model mismatch due to the high process nonlinearity, rendering successive linearization inaccurate. The NMPC strategy shows good overall robustness for two different control objectives, which were both within 7% of their optimal values, while satisfying all constraints on manipulated and state variables within the specified batch time. © 2009 American Institute of Chemical Engineers AIChE J, 2009 [source] Robust iterative learning control design for batch processes with uncertain perturbations and initializationAICHE JOURNAL, Issue 6 2006Jia Shi Abstract A robust iterative learning control (ILC) scheme for batch processes with uncertain perturbations and initial conditions is developed. The proposed ILC design is transformed into a robust control design of a 2-D Fornasini,Marchsini model with uncertain parameter perturbations. The concepts of robust stabilities and convergences along batch and time axes are introduced. The proposed design leads to nature integration of an output feedback control and a feedforward ILC to guarantee the robust convergence along both the time and the cycle directions. This design framework also allows easy enhancement of the feedback and/or feedforward controls of the system by extending the learning information along the time and/or the cycle directions. The proposed analysis and design are formulated as matrix inequality conditions that can be solved by an algorithm based on linear matrix inequality. Application to control injection packing pressure shows the proposed ILC scheme and its design are effective. © 2006 American Institute of Chemical Engineers AIChE J, 2006 [source] | ||||||||||