Abstract: State and parameter estimation in nonlinear systems is a challenging research topic. To date, there is no general solution for the state and parameter estimation of the nonlinear system which makes it an active field of research. Although there is no general ’go-to’ method, some methods are widely used. The extended Kalman filter is one of them. Despite being popular, it suffers from major drawbacks mostly caused by linearization which is overcome by development of unscented Kalman filter. In this paper these two methods are described alongside with least square estimation and estimation based on disturbance observer. Application to state and parameter estimation of the unmanned aerial vehicle (UAV) with suspended load is presented which due to the complexity of the nonlinear dynamics, present many challenges from the control point of view. One of the biggest are the oscillations caused by the swinging load that may bring system into self-oscillations and instability. To deal with this challenge, position of the slung load relative to the aircraft must be determined. This is the main focus of the current research and this paper.
Index Terms—State and parameter estimation, aerial load manipulation, nonlinear estimation, disturbance observer.
