Nonlinear MPC for a Sensorless Multi‐Vectored Propeller Airship Based on Sliding Mode Observer with Saturation

Abstract

A nonlinear fault tolerant station keeping controller for a multi-vectored propeller airship without velocity and angular velocity sensors is developed, which is composed of three modules: nonlinear model predictive controller (NMPC), sliding mode observer (SMO), and linear programming (LP) based control allocation. The kinematics and dynamics model of the airship are introduced. Based on the nonlinear model, with the assumption that the velocity and angular velocity sensors are damaged, a sliding mode observer is designed to estimate the velocity and angular velocity of the airship. To achieve good performance in the station keeping mission, an explicit nonlinear model predictive control is derived. A linear programming base control allocation method is proposed to solve both amplitude and rate constraint of the propulsion forces and deflection angles. Stability analysis is carried out to prove that the system can be stabilized in finite time. Simulation results for the station keeping control are illustrated to prove the effectiveness of the proposed method.

Estimation of Airship Aerodynamic Forces and Torques Using Extended Kalman Filter

“…While I 6×6 is an identity matrix. The continuous-time state equation representing airship dynamics is given in (7). Here its compact representation can be given bẏ…”

“…A vast number of control methods including Sliding Mode Control (SMC) [2]- [4], Nonlinear Model Predictive Controller (NMPC) [7], gain scheduling control [8], etc have been…”

Composite nonlinear feedback with dynamic event‐triggered mechanism for control systems in the presence of saturation nonlinearity

“…This phenomenon is usually called saturation. There are many ways to handle saturation, such as circle criterion and Popov criterion within the absolute stability framework [1], quadratic approach based on convex polyhedron and dead zone function [2, 3], low gain feedback control [4–6], anti‐windup compensator synthesis [7], linear programming based saturation suppression strategy [8], and so on.…”

Unscented Kalman filtering for nonlinear systems with sensor saturation and randomly occurring false data injection attacks

“…On another research frontier, sensors may not always be capable of providing signals with unlimited amplitudes due to physical/technological restrictions. Phenomenon of the saturation usually happens in practical physical systems, which seriously affects system performance and even makes the filter unstable [15–18]. Thus, the saturation problem has been considered for state estimation problems in some existing literatures [19–23].…”