State Feedback Control of Asynchronous Machines with Nondeterministic Models

This note is concerned with control of input/state asynchronous sequential machines with nondeterministic models. The objective is to use state feedback for controlling the machine so as to match any possible behavior of the model. When exact model matching is unsolvable, the model matching inclusion problem is considered in which we find the supremal controllable sub-model, or the largest sub-model of a given nondeterministic model that can be matched by the closed-loop system.      

Input-state model matching and ripple-free response for dual-rate systems

In this paper, we address the model matching problem for dual-rate systems where the controller output is generated at a faster rate than the measurement update rate. The model matching problem that has been studied in the literature requires the input-output properties of the closed-loop multirate system to match those of a desired single-rate linear time-invariant (LTI) system. In this paper, we consider the model matching problem from the input-state viewpoint: given a desired LTI system, find conditions and provide a controller design procedure to achieve matching between the closed-loop system and the desired system state variables at the measurement update rate. We provide a solution to this problem using a particular time-varying controller structure. In addition, we give conditions to avoid ripples in the steady-state output of the continuous-time plant; in particular, we show that some constraints on the input matrix of the desired system have to be posed. Numerical examples are given to illustrate the proposed method.     

Asymptotic model matching for nonlinear systems

This paper investigates the problem of designing a compensating control law for a square invertible nonlinear plant so that the response of the closed-loop system asymptotically matches that of a prescribed, driven, nonlinear model. A set of necessary conditions for achieving asymptotic model matching is established. One of these involves the stability properties for subdynamics which are common to every model matching closed loop. These subdynamics, called the “fixed dynamics,” are intrinsically characterized. Based on these results, a new set of sufficient conditions for achieving asymptotic model matching is given. The interrelation between the minimum-phase and vector relative degree properties of a plant and a matchable model are studied     

不确定非线性系统的鲁棒耗散性与保性能控制

考虑了不确定仿射非线性系统的鲁棒耗散性与保性能控制问题,不确定性范数有界,不满足匹配条件.基于HJI不等式,设计了状态反馈控制器.当扰动存在时,控制器能使系统达到耗散,当扰动为零时,所设计的控制器使系统对于给定的性能函数具有上界,最后研究了不确定线性系统的保性能与耗散性控制情形.     

Robust ℋ2/ℋ∞/reference model dynamic output-feedback control synthesis

This article presents a new strategy to design robust model matching dynamic output-feedback controllers that guarantee tracking response specifications, disturbance rejection and noise attenuation. The proposed synthesis methodology, based on a multi-objective optimisation problem, can be applied to uncertain continuous or discrete-time linear time-invariant systems with polytopic uncertainty, leading to both full-order and reduced-order robust-performance dynamic controllers. The objective functions represent the ?_∞-norm of the difference between the closed-loop transfer function matrix, from the reference signals and the plant outputs and the reference model matrix, the ?_∞-norm of the closed-loop transfer function matrix from the disturbances and the plant outputs and the ?₂-norm of the closed-loop transfer function matrix from the measurement noises and the control inputs. An integral control action is also introduced in order to achieve zero steady-state error. In the case of MIMO systems, the proposed strategy can be applied to decouple the closed-loop control system choosing an appropriated reference model matrix. Two examples are presented to illustrate both SISO and MIMO systems control synthesis.     

Estimating performance of the robust control system under unknown upper disturbance boundaries and measurement noise

Consideration was given to estimation of the robust performance of the closed-loop control system under unknown upper disturbance boundaries. The linear stationary discrete plant with scalar output and control served as a model of the nominal plant. The disturbances included external bounded disturbance, measurement noise, and operator disturbances in output and control. Consideration was given to calculation of the asymptotic upper boundaries of the measurable and nonmeasurable tracking errors coordinated with the measurement data.     

Model matching inclusion for input/state asynchronous sequential machines

The problem of model matching for asynchronous sequential machines consists of finding a feedback controller for a given open-loop machine so that the resulting closed-loop machine matches a desired model. In this paper, the control objective is extended to model matching inclusion in which the behavior of the closed-loop system should be contained in that of the model. The supremal controllable sub-model is characterized as an asynchronous machine with the largest behavior set contained in a given model that can be matched by the closed-loop machine via state feedback control. An effective computational algorithm is developed and an example is provided for illustration.     

Robust continuous-time adaptive control by parameter projection

The problem of adaptive control of a continuous-time plant of arbitrary relative degree, in the presence of bounded disturbances as well as unmodeled dynamics, is addressed. The adaptation considered is the usual gradient update law with parameter projection, the latter being the only robustness enhancement modification employed. It is shown that if the unmodeled dynamics, which consists of multiplicative as well as additive system uncertainty, is small enough, then all the signals in the closed-loop system are bounded. This shows that extra modifications are not necessary for robustness with respect to bounded disturbances and small unmodeled dynamics. In the nominal case, where unmodeled dynamics and disturbances are absent, the asymptotic error in tracking a given reference signal is zero. Moreover, the performance of the adaptive controller is also robust     

Adaptive actuator failure compensation control for MIMO systems*

Two adaptive failure compensation control schemes based on MRAC are developed for a class of MIMO LTI systems with unknown actuator failures. An effective controller structure is proposed to achieve the desired plant-model output matching when implemented with matching parameters. Design conditions are specified for such nominal plant-model output matching. Two adaptive versions of the nominal controller are proposed and stable adaptive laws are derived for updating the controller parameters when plant parameters and failure parameters are unknown. All closed-loop signals are bounded and the plant outputs track the given reference outputs asymptotically, despite the uncertainties in actuator failures and plant parameters. Simulation results for an aircraft lateral dynamic model verify the desired adaptive control system performance in the presence of unknown rudder and aileron failures.     

The output control of linear time-invariant multivariable systems with unmeasurable arbitrary disturbances

Necessary and sufficient conditions are derived for a minimal order linear time-invariant differential feedback control system to exist for a linear time-invariant multivariable system with unmeasurable arbitrary disturbances of a given class occurring in it, such that the outputs of the system asymptotically become equal to preassigned functions of a given class of outputs, independent of the disturbances occurring in the system, and such that the closed-loop system is controllable. The feedback gains of the control system are obtained so that the dynamic behavior of the closed-loop system is specified by using either an integral quadratic optimal control approach or a pole assignment approach. The result may be interpreted as being a generalization of the single-input, single-output servomechanism problem to multivariable systems or as being a solution to the asymptotic decoupling problem.     

Two-degree-of-freedom ?2-optimal tracking with preview

A simple SISO two-degree-of-freedom pole-placement design method is presented that provides ?₂-optimal tracking of a given reference signal. The closed-loop pole locations are first chosen by the system designer. The closed-loop zeros are then placed in an optimal fashion by a computationally inexpensive algorithm to achieve asymptotic tracking with an optimal transient response. The preview approach, which has become a common method for dealing with systems which have non-minimum phase behavior, can then optionally be used to further improve the transient behavior for both minimum phase and non-minimum phase systems. Unlike previous results based on the preview approach, the solution presented here takes into consideration the closed-loop pole dynamics, and is ?₂ optimal with respect to all other two-degree-of-freedom preview controllers with the same closed-loop poles. A simple solution to the H₂ model matching problem, where the design parameter Q is not rational, but polynomial, is the heart of the solution method.     

Solution of the discrete-time stochastic optimal control problem in the 2-domain

The design of discrete-time optimal multivariate systems is considered in the z-domain. The constant plant can be non-square, unstable and/or non-minimum phase and feedback system dynamics can be modelled. The stationary coloured noise processes are assumed to be represented by discrete rational spectral densities. The system can contain transport delay elements and the effects of plant saturation can be limited by the choice of performance criterion. The system inputs are assumed to contain both stochastic and deterministic components.

The two-stage design procedure is original and it enables the stochastic and deterministic control functions to be separated, A performance criterion is first defined which is insensitive to the deterministic signals and this defines the closed-loop optimal controller. The resulting closed-loop system acts as an optimum regulator to minimize the effects of stochastic disturbances. A second tracking error performance criterion is then specified which determines the optimal reference input to the closed-loop system. This reference signal is generated by two further discrete-time controllers. The first controller ensures that the plant is following a desired trajectory and the second acts as a feedforward controller to counteract measurable disturbances. The minimum variance regulators of Astrom (1970) and Peterka (1972) are also derived from these results.     

The robust control of a servomechanism problem for linear time-invariant multivariable systems

Necessary and sufficient conditions are found for there to exist a robust controller for a linear, time-invariant, multivariable system (plant) so that asymptotic tracking/regulation occurs independent of input disturbances and arbitrary perturbations in the plant parameters of the system. In this problem, the class of plant parameter perturbations allowed is quite large; in particular, any perturbations in the plant data are allowed as long as the resultant closed-loop system remains stable. A complete characterization of all such robust controllers is made. It is shown that any robust controller must consist of two devices 1) a servocompensator and 2) a stabilizing compensator. The servocompensator is a feedback compensator with error input consisting of a number of unstable subsystems (equal to the number of outputs to be regulated) with identical dynamics which depend on the disturbances and reference inputs to the system. The sorvocompensator is a compensator in its own right, quite distinct from an observer and corresponds to a generalization of the integral controller of classical control theory. The sole purpose of the stabilizing compensator is to stabilize the resultant system obtained by applying the servocompensator to the plant. It is shown that there exists a robust controller for "almost all" systems provided that the number of independent plant inputs is not less than the number of independent plant outputs to be regulated, and that the outputs to be regulated are contained in the measurable outputs of the system; if either of these two conditions is not satisfied, there exists no robust controller for the system.     

Linear quadratic output tracking and disturbance rejection

This article introduces the problem of linear quadratic tracking (LQT) where the objective is to design a closed-loop control scheme such that the output signal of the system optimally tracks a given reference signal and rejects a given disturbance. Different performance indices that have been used to address the tracking problem are discussed and an appropriate new form is introduced. It is shown that a solution to the proposed optimality index exists under very mild conditions of stabilisability and detectability of the plant state-space equations. The solution is formulated based on converting the LQT problem to a standard linear quadratic regulation problem. The method is applied to two examples, a first-order plant and a third-order plant, and their simulation results are presented and discussed.     

Adaptive control of rigid body satellite

The minimal controller synthesis （MCS） is an extension of the hyperstable model reference adaptive control algorithm. The aim of minimal controller synthesis is to achieve excellent closed-loop control despite the presence of plant parameter variations, external disturbances, dynamic coupling within the plant and plant nonlinearities. The minimal controller synthesis algorithm was successfully applied to the problem of decentralized adaptive schemes. The decentralized minimal controller synthesis adaptive control strategy for controlling the attitude of a rigid body satellite is adopted in this paper. A model reference adaptive control strategy which uses one single three-axis slew is proposed for the purpose of controlling the attitude of a rigid body satellite. The simulation results are excellent and show that the controlled system is robust against disturbances.     

Adaptive compensation strategy for the tracking/rejection of signals with time-varying frequency in digital repetitive control systems

Digital repetitive control is a technique which allows to track periodic references and/or reject periodic disturbances. Repetitive controllers are usually designed assuming a fixed frequency for the signals to be tracked/rejected, its main drawback being a dramatic performance decay when this frequency varies. A common approach to overcome this problem consists of an adaptive change of the sampling time according to reference/disturbance period variations. However, the sampling period adaptation implies structural changes that may degrade the closed-loop time response. This article presents a design strategy which allows to compensate for the effect of non-uniform sampling and forces the closed-loop behavior to coincide with that of the system operating under an a priori selected nominal sampling period. The stability of the overall closed-loop system is also analyzed. Experimental results obtained from a mechatronic plant model validate the proposal.     

Model matching with strong stability in switched linear systems

This work deals with model matching by output dynamic feedback in switched linear systems. The plant and the model are assumed to be subject to different switching signals. A necessary and sufficient condition for achieving model matching with asymptotic stability of both the closed-loop compensated system and the compensator, for a sufficiently large dwell time, is proven. Such condition is obtained by specializing the structural condition with a suitable redefinition of the robust controlled invariant subspace involved, capable of capturing not only the structural aspect of the problem but also the stability aspects. The effect of the combined action of nonzero initial states and nonzero inputs is dealt with. The solution to a more demanding problem formulation, where the dwell time is assumed to be fixed and given is also discussed.     

Robust adaptive control in the presence of bounded disturbances

The model reference adaptive control of a linear plant subjected to bounded disturbances is considered. By analyzing a set of nonlinear differential equations, it is shown that the global behavior of the adaptive system depends upon the persistent excitation of the reference input as well as the amplitude of the external disturbances. The principal contribution of the paper is the derivation of sufficient conditions on the persistent excitation of the reference input, given the maximum amplitude of disturbance, for the signals in the adaptive system to be globally bounded.     

On the supremal controllable sublanguage in the discrete-eventmodel of nondeterministic hybrid control systems

This paper is concerned with the logical control of hybrid control systems (HCS). It is assumed that a discrete-event system (DES) plant model has already been extracted from the continuous-time plant. The problem of hybrid control system design can then be solved by applying logical DES controller synthesis techniques to the extracted DES plant. Traditional DES synthesis methods, however, are not always applicable since the extracted plant DES will often exhibit nondeterministic transitions. This paper presents an extension of certain DES controller synthesis techniques to the nondeterministic control automaton found in HCS. In particular, this paper derives a formula computing the supremal controllable sublanguage of a given specification language under the assumption that the DES plant exhibits nondeterministic transitions