A comparison of nonlinear control performance assessment techniques for nonlinear processes

A Comparison of Nonlinear Control Performance Assessment Techniques for Nonlinear Processes

Assessing the quality of industrial control loops is an important auditing task for the control engineer. However there are complications when considering the ubiquitous nonlinearities present in many industrial control loops. If one simply ignores these nonlinearities, there is the danger of over-estimating the performance of the control loop in rejecting disturbances, and thereby possibly ove...

Nonlinear Optimal Control Techniques Applied to a Launch Vehicle Autopilot

This paper presents an application of the nonlinear optimal control techniques to the design of launch vehicle autopilots. The optimal control is given by the solution to the Hamilton-Jacobi-Bellman (HJB) equation, which in this case cannot be solved explicity. A method based upon Successive Galerkin Approximation (SGA), is used to obtain an approximate optimal solution. Simulation results invo...

application of affine gray-box neural models for nonlinear control of chemical processes

assessment of the park- ang damage index for performance levels of rc moment resisting frames

چکیده هدف اصلی از طراحی لرزه ای تامین ایمنی جانی در هنگام وقوع زلزله و تعمیر پذیر بودن سازه خسارت دیده، پس از وقوع زلزله است. تجربه زلزله های اخیر نشان داده است که ساختمان های طراحی شده با آیین نامه های مبتنی بر نیرو از نظر محدود نمودن خسارت وارده بر سازه دقت لازم را ندارند. این امر سبب پیدایش نسل جدید آیین نامه های مبتنی بر عملکرد شده است. در این آیین نامه ها بر اساس تغییرشکل های غیرارتجاعی ...

Empirical Performance Assessment of Nonlinear Model Selection Techniques

Estimating Prediction Risk is important for providing a way of computing the expected error for predictions made by a model, but it is also an important tool for model selection. This paper addresses an empirical comparison of model selection techniques based on the Prediction Risk estimation, with particular reference to the structure of nonlinear regularized neural networks. To measure the pe...