Generalized Nonlinear Complementary Attitude Filter

This work describes a family of attitude estimators that are based on a generalization of Mahony's nonlinear complementary filter. This generalization reveals the close mathematical relationship between the nonlinear complementary filter and the more traditional multiplicative extended Kalman filter. In fact, the bias-free and constant gain multiplicative continuous-time extended Kalman filters may be interpreted as special cases of the generalized attitude estimator. The correspondence provides a rational means of choosing the gains for the nonlinear complementary filter and a proof of the near global asymptotic stability of special cases of the multiplicative extended Kalman filter

Geometrically Intrinsic Nonlinear Recursive Filters I: Algorithms

The Geometrically Intrinsic Nonlinear Recursive Filter, or GI Filter, is designed to estimate an arbitrary continuous-time Markov diffusion process X subject to nonlinear discrete-time observations. The GI Filter is fundamentally different from the much-used Extended Kalman Filter (EKF), and its second-order variants, even in the simplest nonlinear case, in that: (i) It uses a quadratic function of a vector observation to update the state, instead of the linear function used by the EKF. (ii) It is based on deeper geometric principles, which make the GI Filter coordinate-invariant. This implies, for example, that if a linear system were subjected to a nonlinear transformation f of the state-space and analyzed using the GI Filter, the resulting state estimates and conditional variances would be the push-forward under f of the Kalman Filter estimates for the untransformed system - a property which is not shared by the EKF or its second-order variants. The noise covariance of X and the observation covariance themselves induce geometries on state space and observation space, respectively, and associated canonical connections. A sequel to this paper develops stochastic differential geometry results - based on "intrinsic location parameters", a notion derived from the heat flow of harmonic mappings - from which we derive the coordinate-free filter update formula. The present article presents the algorithm with reference to a specific example - the problem of tracking and intercepting a target, using sensors based on a moving missile. Computational experiments show that, when the observation function is highly nonlinear, there exist choices of the noise parameters at which the GI Filter significantly outperforms the EKF.Comment: 22 pages, 4 figure

Comparisons of nonlinear estimators for wastewater treatment plants

This paper deals with five existing nonlinear estimators (filters), which include Extended Kalman Filter (EKF), Extended H-infinity Filter (EHF), State Dependent Filter (SDF), State Dependent H-Infinity Filter (SDHF) and Unscented Kalman Filter (UKF) that are formulated and implemented to estimate unmeasured states of a typical biological wastewater system. The performance of these five estimators of different complexities, behaviour and advantages are demonstrated and compared via nonlinear simulations. This study shows promising application of UKF for monitoring and control of the process variables, which are not directly measurable

Nonlinear Performance of BAW Filters Including BST Capacitors

This paper evaluates the nonlinear effects occurring in a bulk acoustic wave (BAW) filter which includes barium strontium titanate (BST) capacitors to cancel the electrostatic capacitance of the BAW resonators. To do that we consider the nonlinear effects on the BAW resonators by use of a nonlinear Mason model. This model accounts for the distributed nonlinearities inherent in the materials forming the resonator. The whole filter is then implemented by properly connecting the resonators in a balanced configuration. Additional BST capacitors are included in the filter topology. The nonlinear behavior of the BST capacitors is also accounted in the overall nonlinear assessment. The whole circuit is then used to evaluate its nonlinear behavior. It is found that the nonlinear contribution arising from the ferroelectric nature of the BST capacitors makes it impractical to fulfill the linearity requirements of commercial filters

A nonlinear filter for compensating for time delays in manual control systems

A nonlinear filter configured to provide phase lead without accompanying gain distortion is analyzed and evaluated. The nonlinear filter is superior to a linear lead/lag compensator in its ability to maintain system stability as open loop crossover frequency is increased. Test subjects subjectively rated the filter as slightly better than a lead/lag compensator in its ability to compensate for delays in a compensatory tracking task. However, the filter does introduce unwanted harmonics. This is particularly noticeable for low frequency pilot inputs. A revised compensation method is proposed which allows such low frequency inputs to bypass the nonlinear filter. A brief analytical and experimental evaluation of the revised filter indicates that further evaluation in more realistic tasks is justified

SIAC Filtering for Nonlinear Hyperbolic Equations

We present the results of the symmetric and one-sided Smoothness-Increasing Accuracy-Conserving (SIAC) filter applied to a discontinuous Galerkin (DG) approximation for two examples of nonlinear hyperbolic conservation laws. The traditional symmetric SIAC filter relies on having a translation invariant mesh, periodic boundary conditions and linear equations. However, for practical applications that are modelled by nonlinear hyperbolic equations, this is not feasible. Instead we must concentrate on a filter that allows error reduction for nonuniform/unstructured meshes and non-periodic boundary conditions for nonlinear hyperbolic equations. This proceedings is an introductory exploration into the feasibility of these requirements for efficient filtering of nonlinear equations