Design of Luenberger function observer with disturbance decoupling for matrix second-order linear systems-a parametric approach

A simple method for disturbance decoupling for matrix second-order linear systems is proposed directly in matrix second-order framework via Luenberger function observers based on complete parametric eigenstructure assignment. By introducing the H2 norm of the transfer function from disturbance to estimation error, sufficient and necessary conditions for disturbance decoupling in matrix second-order linear systems are established and are arranged into constraints on the design parameters via Luenberger function observers in terms of the closed-loop eigenvalues and the group of design parameters provided by the eigenstructure assignment approach. Therefore, the disturbance decoupling problem is converted into an eigenstructure assignment problem with extra parameter constraints. A simple example is investigated to show the effect and simplicity of the approach.

ALMOST DISTURBANCE DECOUPLING FOR A CLASS OF MINIMUM-PHASE HIGHER-ORDER CASCADE NONLINEAR SYSTEMS

The problem of almost disturbance decoupling (ADD) with internal stability is discussed, for a class of high_order cascade nonlinear systems having zero dynamics. Using adding power integrator techniques, the ADD problems via a smooth static state feedback is solved.

Almost Disturbance Decoupling for HOFA Nonlinear Systems with Strict-Feedback Form

The article is devoted to the almost disturbance decoupling problem for high-order fully actuated(HOFA)nonlinear systems with strict-feedback form.Using the full-actuation feature of high-order fully actuated systems and Lyapunov stability theory,a state feedback control law and virtual control laws are designed.The unknown disturbances are handled by almost disturbance decoupling(ADD)method.Finally,the effectiveness of the control strategy is verified by stability analysis and simulation.

A NOTE ON NONLINEAR ROBUST H_∞ ALMOST DISTURBANCE DECOUPLING PROBLEM WITH STABILITY

For a class of SISO nonlinear control systems with parameter uncertainty an almost disturbance decoupling problem with stability is defined and investigated. Back stepping technique provides a practical design method of controller, under which the $L2$ gain from the disturbance to the controlled output can be arbitrarily small subject to nonlinear uncertainties and the close-loop system is internally asymptotically stable.

DESIGN OF DISTURBANCE DECOUPLED FILTER AND ITSAPPLICATION TO MANEUVERING TARGETS TRACKING

A novel disturbance decoupled filter (DDF) design scheme is presented. Firstly, the system with unknown input is translated into an equivalent system without unknown imputs by a simple algebraic transformation. Then, a new DDF design scheme, which is very simple, is proposed via innovations theorem. At last, the application of DDF to Maneuvering Targets Tracking is simulated and the simulation results show that DDF is suitable for high maneuvering cases.

Asurvey onob vabilit of Boolean control networks

Observability is a fundamental property of a partially observed dynamical system,which means whether one can use an input sequence and the corresponding output sequence to determine the initial state.Observability provides bases for many related problems,such as state estimation,identification,disturbance decoupling,controller synthesis,etc.Until now,fundamental improvement has been obtained in observability of Boolean control networks(BCNs)mainly based on two methods-Edward F.Moore's partition and our observability graph or their equivalent representations found later based on the semitensor product(STP)of matrices(where the STP was proposed by Daizhan Cheng),including necessary and sufficient conditions for different types of observability,extensions to probabilistic Boolean networks(PBNs)and singular BCNs,even to nondeterministic finite-transition systems(NFTSs);and the development(with the help of the STP of matrices)in related topics,such as com-putation of smallest invariant dual subspaces of BNs containing a set of Boolean functions,multiple-experiment observability verification/decomposition in BCNs,disturbance decoupling in BCNs,etc.This paper provides a thorough survey for these topics.The contents of the paper are guided by the above two methods.First,we show that Moore's partition-based method closely relates the following problems:computation of smallest invariant dual subspaces of BNs,multiple-experiment observ-ability verification/decomposition in BCNs,and disturbance decoupling in BCNs.However,this method does not apply to other types of observability or nondeterministic systems.Second,we show that based on our observability graph,four different types of observability have been verified in BCNs,verification results have also been extended to PBNs,singular BCNs,and NFTSs.In addition,Moore's partition also shows similarities between BCNs and linear time-invariant(LTI)control systems,e.g.,smallest invariant dual subspaces of BNs containing a set of Boolean functions in BCNs vs unobservable subspaces of LTI control systems,the forms of quotient systems based on observability decomposition in both types of systems.However,there are essential differences between the two types of systems,e.g.,"all plausible definitions of observability in LTI control systems turn out to be equivalent"(by Walter M.Wonham 1985),but there exist nonequivalent definitions of observability in BCNs;the quotient system based on observability decomposition always exists in an LTI control system,while a quotient system based on multiple-experiment observability decomposition does not always exist in a BCN.