Time-Delay Margin and Robustness of Incremental Nonlinear Dynamic Inversion Control

Nonlinear dynamic inversion (NDI) is a nonlinear feedback linearization technique that has been widely applied to flight control systems [1,2]. Using state feedback and the inverted nonlinear system dynamics, NDI can significantly reduce controller development costs by avoiding gain scheduling and Jacobian linearization at a multitude of...

Long-Stroke Hydraulic Robot Motion Control With Incremental Nonlinear Dynamic Inversion

High precision motion control of hydraulic manipulators is challenging due to the highly nonlinear dynamics and model uncertainties typical for hydraulic actuators. This paper addresses the implementation of a novel sensor-based incremental nonlinear dynamic inversion control technique for a high-precision hydraulic force controller in existence...

Incremental Nonlinear Dynamic Inversion Control for Hydraulic Hexapod Flight Simulator Motion Systems

Hydraulic driven manipulators face serious control problems due to the nonlinear system dynamics and model and parametric uncertainties of hydraulic actuators. In this paper, a novel sensor-based Incremental Nonlinear Dynamic Inversion controller is applied to force tracking control of hydraulic actuators of a hexapod flight simulator motion...

Improved Stewart platform state estimation using inertial and actuator position measurements

Accurate and reliable estimation of the kinematic state of a six degrees-of-freedom Stewart platform is a problem of interest in various engineering disciplines. Particularly so in the area of flight simulation, where the Stewart platform is in widespread use for the generation of motion similar to that experienced in actual flight. Accurate...

Piloted simulator evaluation of a model-independent fault-tolerant flight control system

Using iterated extended Kalman Filtering for estimation of a hexapod flight simulator motion state

The six degrees-of-freedom Stewart platform, or hexapod, is in widespread use in the flight simulation industry for the generation of motion cues that are representative of those experienced in actual flight. For closed-loop control of such motion platforms, but also to be able to objectively assess the quality of the generated simulator motion,...

Modeling Human Multimodal Perception and Control Using Genetic Maximum Likelihood Estimation

This paper presents a new method for estimating the parameters of multi-channel pilot models that is based on maximum likelihood estimation. To cope with the inherent nonlinearity of this optimization problem, the gradient-based Gauss-Newton algorithm commonly used to optimize the likelihood function in terms of output error is complemented with...