Design of linear observers for a class of linear hybrid systems

This paper deals with the design of linear observers for a class of linear hybrid systems. Such systems are composed of continuous-time and digital substates and possess, in general, coupling dynamics between both substates. Two observer prototypes based on the prediction error are proposed. The first is based on the observation of an extended discrete system at sampling instants. The discrete extended state is composed of the sampled values of the continuous substate at sampling instants and the digital substate. The estimation of the continuous substate in between sampling instants is made by using the plant parametrization and the sampled prediction error at the preceding sampling instant. The continuous-time state estimates are reinitialized at each new sampling instant by taking values from the corresponding components of the discretized substate of the observer of the auxiliary discrete extended system. The second observer prototype estimates the continuous-time substate for all time from initial conditions which are taken only when the estimation algorithm starts. The observer involves feedback information of the current observation error, that of the preceding sampling instant and that associated with the estimation of the discrete system. As a result, the discontinuities of the estimated substate at sampling instants, which typically occur with the use of the first prototype, are not present in this observation scheme. The exponential convergence to zero of both prediction and observation errors may be ensured under observability and detectability assumptions Furthermore, prescribed pole placement of the state estimation error is achieved under observability of the discrete extended plant. Also, prescribed pole placement of the combined dynamics of the extended plant and observation error can be obtained. For that purpose, the extended hybrid plant is assumed to be controllable when the linear control input is generated from measurements of the state observation. in both observation prototypes.     

A result on the hyperstability of a class of hybrid dynamic systems

This paper presents a hyperstability theorem for a class of hybrid dynamic systems composed of coupled differential and difference equations subject to (possibly) time-varying nonlinearities satisfying a Popov-type inequality. The nonlinear controller generates the plant input at all times from its sampled values by defining an extended discrete system. The hyperstability results are obtained from this discrete system of special type whose state consists of the sampled continuous substate and the digital substate of the given hybrid system. Some corollaries and related physical interpretations are also given     

OBSERVER-BASED HYBRID CONTROL OF SAMPLED-DATA UNCERTAIN SYSTEM WITH INPUT TIME DELAY

This paper proposes a new digital redesign method for determining the hybrid controller of a continuous-time system with input time delay using an observer-based digital controller. The proposed method together with the genetic algorithms is used to determine: (1) the interval digital model of a continuous-time uncertain system with input time delay, (2) the interval digital redesign control law and (3) the interval digital observer of the original continuous-time uncertain observer with input time delay. Moreover, the result is less conservative than those obtained by the existing interval methods. A discrete-time observer is built by the original continuous-time observer with input-time-delay control law and a predictor such that the estimated states of the redesigned discrete-time observer closely match those of the original continuous-time observer with input time delay not only at sampling instants but also the behavior of the system state during the sampling interval is optimal by minimizing the hybrid performance index. The digitally redesigned observer-based controller can closely match the states of the digitally redesigned uncertain sampled-data system with those of the original continuous-time observer-based controlled uncertain system with input time delay.     

A review of: “Actes du Colloque ELABORATION ET JUSTIFICATION DES MODELES”, edited by P. Delattre and M. Thellier. Maloine S.A., Paris, 1979, 2 volumes, 748 pp.

This paper utilizes trapezoidal rule together with Genetic Algorithm (GA) to convert a continuous-time system with input and state delays to an equivalent discrete-time one. A new method has been proposed to construct the hybrid control of sampled-data system with state and input delays via digital redesign which transforms the control law of a continuous-time system with state and input delays into an equivalent one of a sampled-data system so that the states of the digitally controlled sampled-data system closely match those of the originally well-designed continuous-time system for a relatively longer sampling period. An example is given to demonstrate that the proposed digital redesign is superior to the existing ones under a longer sampling period.     

Asymptotic behaviours and stability of zero dynamics in nonlinear discrete-time systems using Taylor approach and multirate input

It is well known that the existence of unstable sampled zero dynamics is recognised as a major barrier in many control problems. When the usual digital control with zero-order hold (ZOH) or fractional-order hold (FROH) input is used, unstable sampled zero dynamics inevitably appear in the discrete-time model even though the continuous-time system with relative degree more than or equal to three is of minimum phase. In this paper, we show how an approximate sampled-data model can be obtained for nonlinear systems by the use of multirate input and hold such as a generalised sample hold function (GSHF) in order that discrete zero dynamics of the resulting model can be arbitrarily placed. Furthermore, the properties of sampled zero dynamics are studied and the conditions for ensuring the stability of sampling zero dynamics of the desired model are derived. The results presented here generalise well-known notion of sampling zero dynamics from the linear case to nonlinear systems, and GSHF can provide some advantages over ZOH or FROH in terms of stability of discrete system zero dynamics.     

Rapprochement between continuous and discrete model reference adaptive control

In the literature to date there is a dichotomy between results on continuous- and discrete-time model reference control. This is highlighted in the case of continuous-time systems having relative degree greater than one. It is known that, for rapid sampling, these systems always give rise to a non-stably invertible discrete-time system and thus discrete model reference control is ruled out. On the other hand, there are many results pertaining to continuous-time model reference control of such systems. This apparent paradox can be resolved by a slight modification to the discrete-time model format as shown later. This alternative model is used to develop a new discrete model reference adaptive control law and a convergence analysis for the algorithm is presented.     

Multirate digital control design of an optimal regulator via singular perturbation theory

In this paper a multirate digital control design of an optimal regulator is investigated via singular perturbation theory. It is shown that the singularity perturbed continuous-time regulator leads, under slow and fast sampling rates, to two different discrete-time versions. They are decomposed into slow and fast subsystems, and then these solutions are combined in a proper way. Within the framework of such a decomposition-coordination principle, a multirate control design is developed naturally. Furthermore, the problem of the asymptotic stability of a multirate controlled system is investigated and the relationship between the original continuous-time version and the multirate controlled version is discussed.     

Discrete modelling of uncertain continuous systems having an interval structure using higher-order integrators

In this paper, a higher-order integrator approach is proposed to obtain an approximate discrete-time transfer function for uncertain continuous systems having interval uncertainties. Because of the simple algebraic operations of this approach, the resulting discrete model is a rational function of the uncertain parameters. The problem of non-linearly coupled coefficients with exponential nature occurring in the exact discretetime transfer function is therefore circumvented. Furthermore, the interval structure of the uncertain continuous-time system is preserved in the resulting discrete model by using this approach. Formulae to obtain the lower and upper bounds for the coefficients of the discrete interval system are derived, so that digital simulation and design for the uncertain continuous systems can be performed by using the available robustness results in the discrete-time domain.     

H∞-optimal controller discretization

A redesign method for discretizing a continuous-time controller is proposed. The resulting hybrid control system, for example with continuous-time plant and discrete-time controller, is stable, and performance including the system's inter-sampling behaviour can be optimized by approximating some chosen reference transfer function of the continuous-time control system. In order to obtain a tractable problem, the continuous-time part of the hybrid system and the reference transfer function are approximated by a discrete-time system with arbitrary fast sampling. After lifting the resulting periodic system, the approximation problem can be formulated as a standard H_∞-problem which is solved using standard software for H_∞-controller design.     

Hybrid state-space fuzzy model-based controller with dual-ratesampling for digital control of chaotic systems

We develop a hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems. A Takagi-Sugeno (TS) fuzzy model is used to model the chaotic dynamic system and the extended parallel-distributed compensation technique is proposed and formulated for designing the fuzzy model-based controller under stability conditions. The optimal regional-pole assignment technique is also adopted in the design of the local feedback controllers for the multiple TS linear state-space models. The proposed design procedure is as follows: an equivalent fast-rate discrete-time state-space model of the continuous-time system is first constructed by using fuzzy inference systems. To obtain the continuous-time optimal state-feedback gains, the constructed discrete-time fuzzy system is then converted into a continuous-time system. The developed optimal continuous-time control law is finally converted into an equivalent slow-rate digital control law using the proposed intelligent digital redesign method. The main contribution of the paper is the development of a systematic and effective framework for fuzzy model-based controller design with dual-rate sampling for digital control of complex such as chaotic systems. The effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic Chua circuit     

Stability condition for sampled data based control of linear continuous switched systems

Most practical systems are continuous in nature but with discrete (sampled) feedback when digital control is utilized. This paper investigates the stabilization problem of switched linear continuous-time systems with sampled data based control. For both known and unknown arbitrary switching processes, on the basis of Lyapunov stability theory, a sufficient global exponential stability condition related to Dwell time and sampling period is established. For the latter case, on-line one-step adaptive estimation algorithm is derived and integrated with sampled feedback for control design. Validation and verification of the established result are conducted through cruise control of train systems.     

Comparative study of discretization zero dynamics behaviors in two multirate cases

It is well known that the existence of unstable zero dynamics is recognized as a major barrier in many control systems. When the usual digital control with zero-order hold (ZOH) or fractional-order hold (FROH) input is used, unstable zero dynamics inevitably appear in the discrete-time model even though the continuous-time system with relative degree more than two is of minimum phase. This paper investigates the zero dynamics, as the sampling period tends to zero, of sampled-data models composed of a generalized sample hold function (GSHF), a continuous-time nonlinear plant and a sampler in cascade. More precisely, we show how an approximate sampled-data model can be obtained for nonlinear systems with two special GSHF cases such that sampled zero dynamics of the resulting model can be arbitrarily placed. Further, two GSHFs with appropriate parameters provide nonlinear zero dynamics as stable as possible, or with improved stability properties even when unstable, for a given continuous-time plant. It is also shown that the intersample behavior arising from the multirate input can be localised by appropriately selecting the design parameters based on the stability condition of the zero dynamics. The results presented here generalize well-known ideas from the linear to nonlinear cases.     

Discrete-time model reference adaptive control for continuous-timesystems using generalized sampled-data hold functions

The generalized sampled-data hold functions approach of P.T. Kabamba (1987) is extended to the control of linear time-invariant systems with unknown parameters. The idea of Kabamba's approach is to periodically sample the plant output and define the control as the sampled output plus a discrete-time reference, each multiplied by an individual modulating function. Such a control makes it possible to assign an arbitrary discrete-time transfer function for the sampled closed-loop system and does not make assumptions on the plant other than controllability and observability. The authors propose an indirect adaptive controller which is based on this approach and estimates the modulating functions online. In particular, the control is modified so that persistent excitation of the continuous-time plant is ensured without making an assumption on the reference signal, and discrete-time asymptotic model-following is nevertheless obtained. The only assumptions on the plant are minimality, for the continuous and sampled plant, and known order     

A delta transform approach to loop gain-phase shaping design of robust digital control systems

This paper addresses the existence of loop gain-phase shaping (LGPS) solutions for the design of robust digital control systems for SISO, minimum-phase, continuous-time processes with parametric uncertainty. We develop the frequency response properties of LGPS for discrete-time systems using the Δ-transform, a transform method that applies to both continuous-time and discrete-time systems. A theorem is presented which demonstrates that for reasonable specifications there always exists a sampling period such that the robust digital control problem has a solution. Finally, we offer a procedure for estimating the maximum feasible sampling period for LGPS solutions to robust digital control problems.     

Gronwall inequality for hybrid systems

The Gronwall inequality, a well-known and useful result both for continuous-time and discrete-time signals, is extended to hybrid signals, namely those that combine continuous time and discrete time. An application of the result to establishing a bounded energy bounded state property for hybrid systems with inputs is provided.     

GMV control of non-linear continuous-time systems including common delays and state-space models

A non-linear generalized minimum variance control law is proposed for the control of non-linear continuous-time multivariable systems with common delays on input and output channels. The quadratic cost index involves both error and control signal costing terms. The solution for the control law is obtained using a non-linear operator representation of the plant and a linear state-equation model for the disturbance and reference models. The reference and disturbance models are represented by linear subsystems. However, the plant model can be in a very general non-linear operator form, which could involve state-space, transfer operators or non-linear function look up tables. The structure of the system and criterion is chosen so that a simple controller structure and solution is obtained. The controller obtained is simple to implement, particularly in one form, which might be considered to be a state-space version of a non-linear Smith predictor. The results are related to those for discrete-time systems but the presence of the transport delay terms complicates the solution rather more in the continuous-time case.     

Hybrid suboptimal control of multi-rate multi-loop sampled-data systems

A hybrid state-space control scheme for suboptimal digital control of a cascaded continuous-time system using dual rate sampling is presented. First, an optimal regional-pole placement technique is utilized to find an optimal state-feedback control law for a subsystem connected in the inner loop of the overall system. Next, the designed analogue control law is converted into an equivalent fast-rate digital control law using the recently developed digital redesign technique. Then, the digitally redesigned subsystem is converted into an equivalent continuous-time model. As a result, the overall continuous-time model can be formulated from the converted analogue subsystem and the rest of the analogue subsystems to be designed. Moreover, the optimal regional-pole placement technique is applied again to the overall continuous-time model in order to obtain the overall analogue state-feedback control law. Finally, the digital redesign technique is employed again to convert the overall analogue control law obtained to an equivalent slow-rate digital control law. For practical implementations of the developed digital control laws with various sampling rates, the existing ideal state reconstructor method is redeveloped to construct the ideal discrete-lime states using multi-rate input-output data. A practical semi-active terminal homing missile is used as an illustrative example to demonstrate the proposed design method.     

Using hybrid automata for set-membership state estimation with uncertain nonlinear continuous-time systems

This paper deals with set-membership state estimation for continuous-time systems from discrete-time measurements, in the unknown but bounded error framework. The classical predictor–corrector approach to state estimation uses interval Taylor methods for solving the prediction phase, which are known to have poor performance in presence of large model or input uncertainty. In this paper, we show how to derive more efficient predictors by using a nonlinear hybridization method which builds hybrid automata to characterize the boundaries of reachable sets. The derived continuous–discrete set-membership predictor–corrector estimator is then tested with simulated data from a bioreactor. Our method is compared to classical continuous-time interval observers and is shown to have promising performance.     

Stability analysis of a class of switched linear systems on non-uniform time domains

This paper deals with the stability analysis of a class of switched linear systems on non-uniform time domains. The considered class consists of a set of linear continuous-time and linear discrete-time subsystems. First, some conditions are derived to guarantee the exponential stability of this class of systems on time scales with bounded graininess function when the subsystems are exponentially stable. These results are extended when considering an unstable discrete time subsystem or an unstable continuous-time subsystem. Some examples illustrate these results.