The paper proposes a method for observer design for a class of nonlinear systems. We decompose the system using a weaker concept than the relative degree. We provide sufficient conditions for global asymptotic stability of the error dynamics. The observer design is carried out by means of a change of coordinates combined with a high gain technique. In particular, our approach results in an obse...

A high gain observer is proposed for a class of multi-output nonlinear systems with unknown inputs in order to simultaneously estimate the whole state as well as the unknown inputs. The gain of this observer does not require the resolution of any dynamical system and is explicitly given. Moreover, its tuning is reduced to the choice of two real numbers. The performances of the proposed observer...

A high gain observer is proposed for a class of multi-output nonlinear systems with unknown inputs in order to simultaneously estimate the whole state as well as the unknown inputs. The gain of this observer does not require the resolution of any dynamical system and is analytically given. Moreover, its tuning is reduced to the choice of two real numbers. The performances of the proposed observ...

In this paper, we build bounded error observers for a common class of partially known bioreactor models. The main idea is to construct hybrid bounded observers "between" high gain observer, which has an adjustable convergence rate but requires perfect knowledge of the model, and asymptotic observer which is very robust towards uncertainty but has a fixed convergence rate. An hybrid bounded erro...

State space based nonlinear model predictive control (NMPC) needs the state for the prediction of the system behavior. Unfortunately, for most applications, not all states are directly measurable. To recover the unmeasured states, typically a stable state observer is used. However, this implies that the stability of the closed-loop should be examined carefully, since no general nonlinear separa...

An unknown input high gain observer based parametric fault detection and isolation scheme is presented. First, a reduced order unknown input high gain observer is derived. Then, using these observers, a fault detection and isolation technique is devised to detect and isolate the parametric fault of a system whose parameters are uncertain to some extent. The proposed FDI algorithm consists of tw...