Exploiting input sparsity for joint state/input moving horizon estimation

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multiple Window Moving Horizon Estimation

Long horizon lengths in Moving Horizon Estimation are desirable to reach the performance limits of the full information estimator. However, the conventional MHE technique suffers from a number of deficiencies in this respect. First, the problem complexity scales at least linearly with the horizon length selected, which restrains from selecting long horizons if computational limitations are pres...

متن کامل

Moving Horizon Estimation for Integrated Navigation Filtering ⋆

This paper presents a nonlinear numerical observer for accurate position, velocity and attitude (PVA) estimation including the accelerometer bias and gyro bias estimation. The Moving Horizon Observer (MHO) processes the accelerometer, gyroscope and magnetometer measurements from the Inertial Measurement Unit (IMU) and the position and velocity measurements from the Global Navigation Satellite S...

متن کامل

Moving horizon estimation for hybrid systems

We propose a state smoothing algorithm for hybrid systems based on Moving Horizon Estimation (MHE) by exploiting the equivalence between hybrid systems modeled in the Mixed Logic Dynamical form and piecewise affine systems. We provide sufficient conditions on the time horizon and the penalties on the state at the beginning of the estimation horizon to guarantee asymptotic convergence of the MHE...

متن کامل

Multirate State Estimation Using Moving Horizon Estimation

In most chemical processes only some measurements are available online while other measurements are available infrequently and often with long delays. Multirate state estimation can optimally combine these different classes of measurements to improve the estimation quality compared to the fast measurements alone. The nature of measurements at different sampling intervals which are subject to de...

متن کامل

Exploiting Sparsity in Widely Linear Estimation

The distribution of complex random signals is typically improper. It has recently been established that conventional strictly linear models are only second order optimum for signals with proper distributions, while so called “widelylinear models” are optimum for the generality of complex signals, both proper and improper. Widely-linear models, however, are over-parameterised when the underlying...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Mechanical Systems and Signal Processing

سال: 2018

ISSN: 0888-3270

DOI: 10.1016/j.ymssp.2017.08.024