Robust Flight Control Using Incremental Nonlinear Dynamic Inversion and Angular Acceleration Prediction

Abstract

This paper presents a flight control strategy based on nonlinear dynamic inversion. The approach presented, called incremental nonlinear dynamic inversion, uses properties of general mechanical systems and nonlinear dynamic inversion by feeding back angular accelerations. Theoretically, feedback of angular accelerations eliminates sensitivity to model mismatch, greatly increasing the robust performance of the system compared with conventional nonlinear dynamic inversion. However, angular accelerations are not readily available. Furthermore, it is shown that angular acceleration feedback is sensitive to sensor measurement time delays. Therefore, a linear predictive filter is proposed that predicts the angular accelerations, solving the time delay and angular acceleration availability problem. The predictive filter uses only references and measurements of angular rates. Hence, the proposed control method makes incremental nonlinear dynamic inversion practically available using conventional inertial measurement units.

Adaptive Incremental Nonlinear Dynamic Inversion for Attitude Control of Micro Air Vehicles

“…(8) from the previous section. This equation has some extra terms compared to previous work [8], because the gyroscopic and angular momentum effects of the rotors are included.…”

“…A proposed method to deal with these measurement delays is predictive filtering [8]. However, the prediction of angular acceleration requires additional modeling.…”

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

“…(11). This feature was analytically proven in (Simplício et al, 2013;Sieberling et al, 2010), showing that the existence of model mismatch ∆G would not influence the linear relation Eq. (12), with a high sampling rate.…”

“…The novel Incremental Nonlinear Dynamic Inversion (INDI) is a less model dependent and more robust technique that has recently been adopted for various control applications (Smeur et al, 2015;Simplício et al, 2013;Sieberling et al, 2010). By calculating the increment of the control input based on the feedback of a state derivative measurement, instead of computing the total command with the modeled state derivatives with an NDI technique, the INDI controller uses less model information and is insensitive to model and parameter uncertainties.…”

Nonlinear Adaptive Flight Control Using Incremental Approximate Dynamic Programming and Output Feedback

“…This is called a model-free approach, because it does not need any a priori model information at the beginning of the algorithm nor on-line identification of nonlinear systems, but only the on-line identified linear model. This control approach was inspired by the ideas and solutions given by several articles [16][17][18][19][20] . It starts with the selection of the value/cost function in a systematic way, 16 and follows by the Linear Approximate Dynamic Programming (LADP) model-free adaptive control approach.…”