Order Unknown Input Observer Research Articles

Asymptotical Consensus of MIMO Linear Multiagent Systems With a Nonautonomous Leader and Directed Switching Topology: A Continuous Approach

In this paper, we investigate the asymptotical consensus tracking problems for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) with directed switching topology and a non-autonomous leader subject to nonzero unknown inputs. First, we design a full order unknown input observer (UIO) based on relative outputs to estimate the relative full states. Based on this UIO, we design a continuous consensus controller by introducing a decay function which remains positive into the term that is used to eliminate the effects of leader's nonzero inputs. And by using the multiple Lyapunov functions (MLFs) method, we prove that asymptotical consensus can be achieved if the average dwell time (ADT) is greater than a positive threshold. Second, we design a continuous consensus controller based on a reduced order UIO that can significantly simplify calculations. Finally, we give two examples about multiple unmanned aerial vehicles (UAVs) to verify the theoretical results. Compared with existing works, the continuous controllers here can not only achieve zero error consensus tracking, but also are chattering free.

Consensus Disturbance Rejection of MIMO Linear Multiagent Systems With Directed Switching Topologies: A Reduced Order Observer Approach

In this brief, consensus disturbance rejection problem is investigated for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) subject to non-vanishing disturbances under directed switching topologies. First, we design a reduced order unknown input observer (UIO) based only on the relative outputs to estimate the relative full states. Then a consensus controller together with a disturbance observer (DO) is designed to achieve the cooperative goal. Second, by using the average dwell time (ADT) method, it is proven that consensus can be achieved if the ADT is greater than a positive threshold, meanwhile the non-vanishing disturbances are attenuated by DO. Finally, theoretical result is verified by performing simulation.

Fractional Order Unknown Inputs Fuzzy Observer for Takagi–Sugeno Systems with Unmeasurable Premise Variables

This paper presents a new procedure for designing a fractional order unknown input observer (FOUIO) for nonlinear systems represented by a fractional-order Takagi–Sugeno (FOTS) model with unmeasurable premise variables (UPV). Most of the current research on fractional order systems considers models using measurable premise variables (MPV) and therefore cannot be utilized when premise variables are not measurable. The concept of the proposed is to model the FOTS with UPV into an uncertain FOTS model by presenting the estimated state in the model. First, the fractional-order extension of Lyapunov theory is used to investigate the convergence conditions of the FOUIO, and the linear matrix inequalities (LMIs) provide the stability condition. Secondly, performances of the proposed FOUIO are improved by the reduction of bounded external disturbances. Finally, an example is provided to clarify the proposed method. The obtained results show that a good convergence of the outputs and the state estimation errors were observed using the new proposed FOUIO.

Reduced order unknown input observer based distributed fault detection for multi-agent systems

This paper is devoted to the problem of distributed fault detection for multi-agent systems. A reduced order unknown input observer based fault detection method is proposed. By constructing reduced order unknown input observers in one agent, the fault in its neighbor can be detected. In the observer design process, only the measurement output of the neighbor agents is used. Two cases are considered. For the case that the observer matching condition is satisfied, the influence of unknown input on residual is removed completely; if this condition is not satisfied, the influence of a part of unknown input is removed, and the influence of the other part is attenuated. Compared with the existing results, the overall dimension of all the observers is decreased greatly. At last, two examples are given to show the effectiveness of the fault detection method.

Modélisation d'observateurs pour la détection de fautes actionneurs et la localisation de fautes de mesure. Détection et localisation de fautes actionneurs

A new design procedure of a reduced order unknown input observer (UIO) is proposed to generate residuals for fault detection isolation. The originality of this work consists in the chosen approach for the procedure implementation. Indeed the kernel of the actuator fault distribution matrix is generated thanks to generalized inverses. Residual sensivity linked to the constant faults can be set up to facilitate the design of the fault decision stage. Residuals generated by a bank of observers allow the detection isolation of every actuator fault on the one hand and the isolation between actuator faults and sensor faults on the other hand.

A combined observer and filter based approach for the determination of unknown parameters

We consider the simultaneous reconstruction of the state vector and unknown parameters for a special class of non-linear parameter-dependent systems. The approach suggested here consists of two stages. First, the state is reconstructed by a reduced order unknown input observer. Second, this observer is augmented by a filter to obtain the desired parameter. The design procedure is straightforward and may be used for an online estimation of the unknown parameter. In contrast to previous work on adaptive systems, we do not require a persistence of excitation. The approach is illustrated on two non-linear cell models.

New residual generation design for fault detection

Abstract A new design procedure of a reduced order unknown input observer (UIO) is proposed to generate residuals for fault detection isolation (FDI). The originality of this work consists in the adopted approach for the procedure implementation. Indeed the kernel of the actuator fault distribution matrix is generated thanks to generalized inverses. The Kronecker product is used to solve a Sylvester equation which appears in the equations of an UIO. Residuals generated by bank of observers allow on the one hand the detection isolation of every actuator fault and on the other hand the isolation between actuator faults and sensor faults.

Disturbance localization and pole shifting by dynamic compensation

This paper concerns the problem of disturbance localization and pole shifting by dynamic compensation in multivariable linear systems with inaccessible state vector. A necessary and sufficient condition for the solvability of the problem is given. Two synthesis procedures of the compensator are presented: one is based on an observer and the other is based on a dual observer. The observer designed by the proposed procedure acts as as unknown input observer for a linear function. An improved procedure of designing a reduced order unknown input observer is also given. The result may be applicable to reducing the compensator order.