A parameter estimation scheme for a class of sequential hybrid systems

It may happen that the equations governing the response of dynamical systems have some parameters whose values may not be known a priori and have to be obtained using parameter estimation schemes. In this article, we present a parameter estimation scheme for a class of sequential hybrid systems. By hybrid systems, we refer to those systems whose response is described by different governing equations corresponding to various regimes/modes of operation along with some criteria to switch between the same. In a sequential hybrid system, the different modes are arranged in a specific sequence and the system can switch from a given mode to either the previous mode or the following mode in this sequence. Here, we consider those systems whose governing equations consist of ordinary differential equations and algebraic equations. The conditions for switching between the various modes (referred to as transition conditions) are in the form of linear inequalities involving the system output. We shall first consider the case where the transition conditions are known completely. We present a parameter update scheme along with sufficient conditions that will guarantee bounded parameter estimation errors. Then, we shall consider the case where the transition conditions are not known in the sense that some parameters in these conditions are not known. We present a parameter estimation scheme for this case. We illustrate the performance of the parameter estimation scheme in both cases with some examples.     

D-admissible hybrid control of a class of singular systems

This paper mainly studies the problem of designing a hybrid state feedback D-admissible controller for a class of linear and nonlinear singular systems. Based on the relationship between singular discrete systems and singular delta operator systems, several necessary and sufficient conditions for a linear singular delta operator system to be D-admissible (i.e. regular, causal and all finite poles lie in a prescribed circular region) with different representations are derived. Then, the existence conditions and explicit expressions of a desirable D-admissible controller are given by means of matrix inequalities and strict linear matrix inequalities, respectively. We further extend the obtained results to singular delta operator systems with Lipschitz nonlinear perturbations, and the design methods of hybrid controller are presented for the nonlinear case as well. Finally, numerical examples as well as simulations are provided to illustrate the effectiveness of the theoretical outcomes obtained in the paper.     

Stabilizability of a class of stochastic bilinear hybrid systems

The problem of the stabilizability of stochastic nonlinear hybrid systems with a Markovian or any switching rule is considered. Using the Lyapunov technique sufficient conditions for the asymptotic stabilizability in probability by a smooth controller in every structure are found. In particular, the asymptotic stabilizability in probability problem of stochastic bilinear hybrid systems with a Markovian or any switching rule is discussed and a closed-loop controller is found. Also the sufficient conditions for the exponential mean-square stabilizability for bilinear hybrid systems with any switching based on the Lie algebra approach are formulated and an open-loop controller is designed. The obtained results are illustrated by examples and simulations.     

Recursive state estimation for hybrid systems

The paper deals with recursive state estimation for hybrid systems. An unobservable state of such systems is changed both in a continuous and a discrete way. Fast and efficient online estimation of hybrid system state is desired in many application areas. The presented paper proposes to look at this problem via Bayesian filtering in the factorized (decomposed) form. General recursive solution is proposed as the probability density function, updated entry-wise. The paper summarizes general factorized filter specialized for (i) normal state-space models; (ii) multinomial state-space models with discrete observations; and (iii) hybrid systems. Illustrative experiments and comparison with one of the counterparts are provided.     

On the stability of a class of nonlinear hybrid systems

In this paper, we propose new conditions for guaranteeing the stability of nonlinear sampled data systems. In order to do this, we extend Lyapunov theory to this class of systems.     

On the stability of a class of nonlinear hybrid systems

In this paper, we propose new conditions for guaranteeing the stability of nonlinear sampled data systems. In order to do this, we extend Lyapunov theory to this class of systems.     

Robust global recurrence for a class of stochastic hybrid systems

We study a weak property called recurrence for a class of stochastic hybrid systems and establish robustness of the recurrence property. In particular, we establish that recurrence of an open, bounded set is robust to sufficiently small perturbations in the set, perturbations of the data of the stochastic hybrid system and modifications to the system data that slow down the recurrence property. The robustness results are a consequence of the mild regularity properties assumed for the stochastic hybrid system.     

Qualitative fault tolerance analysis for a class of hybrid systems

This paper investigates the fault tolerance problem of hybrid systems with faults that affect the switching sequence. A hierarchical model is developed, which consists of four parts from bottom to top: hybrid automata, qualitative abstraction, discrete abstraction, and supervisor. Under this model, the reachability and fault tolerability properties of hybrid systems can be analyzed in a qualitative manner and from discrete-event system point of view. Sufficient conditions are given to maintain the system’s ideal (or acceptable) performance in spite of faults. Several numerical examples and an application to hose insertion task illustrate the efficiency of the proposed method.     

Fault diagnosis for a class of nonlinear uncertain hybrid systems

This paper presents a fault diagnosis architecture for a class of hybrid systems with nonlinear uncertain time-driven dynamics, measurement noise, and autonomous and controlled mode transitions. The proposed approach features a hybrid estimator based on a modified hybrid automaton framework. The fault detection scheme employs a filtering approach that attenuates the effect of the measurement noise and allows tighter mode-dependent thresholds for the detection of both discrete and parametric faults while guaranteeing no false alarms due to modeling uncertainty and mode mismatches. Both the hybrid estimator and the fault detection scheme are linked with an autonomous guard events identification (AGEI) scheme that handles the effects of mode mismatches due to autonomous mode transitions and allows effective mode estimation. Finally, the fault isolation scheme anticipates which fault events may have occurred and dynamically employs the appropriate isolation estimators for isolating the fault by calculating suitable thresholds and estimating the parametric fault magnitude through adaptive approximation methods. Simulation results from a five-tank hybrid system illustrate the effectiveness of the proposed approach.     

Toward unified analysis and controller synthesis for a class of hybrid systems

This work defines a new class of hybrid systems called state-based switched (SBS) systems that have numerous important engineering applications. The characterizing feature of these systems is that the discrete-event dynamics are associated with the continuous-time state making a specific function be equal to zero. The choice of this function is application specific and for the closed-loop SBS systems defined in this paper it is related to the execution of a desired set of tasks from a pre-specified mission plan. For this broad class of SBS systems, the paper presents a unified analysis and controller synthesis methodology based on Lyapunov theory. Depending on the details of the mission plan, the closed-loop hybrid system will be divided into two subclasses: sequential and non-sequential. The controller design procedure for both subclasses consists of the same two steps: finding a control law and finding a stabilizing switching rule. For static state and output feedback of sequential hybrid systems, the paper proposes a new hybrid sequential sliding-mode controller. It is proven that the control mission can be accomplished for sequential hybrid systems under static state and output feedback using this new controller. A similar framework is investigated for the more complex class of nonsequential hybrid systems and a systematic procedure for designing the switching rule is presented for some specific instances of these systems.     

On asymptotic optimization of a class of nonlinear stochastic hybrid systems

We consider the problem of control for continuous time stochastic hybrid systems in finite time horizon. The systems considered are nonlinear: the state evolution is a nonlinear function of both the control and the state. The control parameters change at discrete times according to an underlying controlled Markov chain which has finite state and action spaces. The objective is to design a controller which would minimize an expected nonlinear cost of the state trajectory. We show using an averaging procedure, that the above minimization problem can be approximated by the solution of some deterministic optimal control problem. This paper generalizes our previous results obtained for systems whose state evolution is linear in the control.This work is supported by the Australian Research Council. All correspondence should be directed to the first author.     

Stabilization of a class of hybrid systems arising in flexible spacecraft

We consider the problem of rigorous modelling of flexible spacecraft and their stabilization. It is shown that the dynamics of the flexible spacecraft can be described by a coupled system of ordinary differential equations and partial differential equations (hybrid system). Lyapunov's approach is used to prove the stabilizability of the system. Simple feedback controls are suggested for stabilization of flexible spacecraft.This work was supported in part by the Natural Science and Engineering Research Council of Canada under Grant No. A7109. The authors would like to thank Professor L. Meirovitch and the reviewers for some valuable suggestions.     

Robust synchronization of a class of chaotic systems with disturbance estimation

This paper investigates the robust synchronization problem for a class of chaotic systems with external disturbances. By using disturbance-observer-based control (DOBC) and LMI approach, the disturbance observers are developed to ensure the boundedness of the disturbance error dynamical. Then, by employing the sliding mode control technique, an adaptive control law is established to eliminate the effect of disturbance error to realize synchronization between the master and slave systems. Finally, the corresponding numerical simulations are demonstrated to verify the effectiveness of proposed method.     

Algebraic switching time identification for a class of linear hybrid systems

In this paper, a method for the finite time estimation of the switching times in linear switched systems is proposed. The approach is based on algebraic tools and distribution theory. Switching time estimates are given by explicit algebraic formulae that can be implemented in a straightforward manner using standard tools from computational mathematics. Simulations illustrate the proposed techniques.     

Identification of plastic material parameters with error estimation

In recent years, inverse analysis has become a common approach to typical engineering problems such as model identification. In this contribution, the inverse problem is discussed in light of taking experimental uncertainties into account. This involves in particular the propagation of experimental errors and the analysis of the sensitivity of the model response to variations in the model parameters to be determined. The method is applied to an elasto-viscoplastic material model which is used in the context of electromagnetic high-speed forming. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Estimation of the domain of attraction for a class of hybrid systems

The problem of the estimation of the domain of attraction for Impulsive Dynamical Systems (IDSs) is tackled in this paper. IDSs are a special class of hybrid systems that exhibit jumps in the state trajectory, which can be either time-driven (time-dependent IDSs), or driven by specific state values (state-dependent IDSs). Sufficient conditions to determine whether a polytope belongs to the domain of attraction of the zero equilibrium point are provided for both time-dependent and state-dependent IDS, when a nonlinear quadratic continuous-time dynamic is considered. The proposed results are stated in terms of Linear Matrix Inequalities problems. The effectiveness of the proposed results is shown by means of the analysis of a biological model for tumor progression.     

Identification of a class of hybrid dynamic systems with feed-forward neural networks: About the validity of the global model

This paper addresses the problem of the identification of a class of Hybrid Dynamic System (HDS). The class herein considered is characterised by continuous inputs, continuous outputs and binary discrete inputs. The proposed approach focuses the attention on the identification of a global model that predicts the continuous outputs of the HDS. The accuracy of this global model is discussed and several simulation examples are investigated in order to study the validity of the obtained neural network global model. The originality of this approach consists in the identification of a HDS without needing to cluster the data or to know the current mode because it considers the identification of HDS in terms of the architectures and the learning algorithms developed for Feed-Forward neural networks.     

Robust state estimation and fault diagnosis for uncertain hybrid systems

Robust state estimation and fault diagnosis are challenging problems in the research into hybrid systems. In this paper a novel robust hybrid observer is proposed for a class of hybrid systems with unknown inputs and faults. Model uncertainties, disturbances and faults are represented as structured unknown inputs. The robust hybrid observer consists of a mode observer for mode identification and a continuous observer for continuous state estimation and mode transition detection. It is shown that the mode can be identified correctly and the continuous state estimation error is exponentially uniformly bounded. Robustness to model uncertainties and disturbances can be guaranteed for the hybrid observer by disturbance decoupling. Furthermore, the detectability and mode identifiability conditions are rigorously analyzed. On the basis of the robust hybrid observer, a robust fault detection and isolation scheme is presented also in the paper. Simulations of a hybrid four-tank system show the proposed approach is effective.     

Local parameter identifiability for one class of hybrid systems

We consider the problem of local parameter identifiability for a hybrid system with components that are continuous and discrete in time. The set of observations is the vector-solution (depending on the parameter that is continuous in time) of the discrete component. Sufficient conditions of local parameter identifiability have been formulated using the earlier introduced notion of normalized separability of the set of parameters from the kernel of a special functional. An example where the condition of normed separability is reduced to some rank criterion is given.