Design of sampled-data critical control systems with persistent/transient inputs using lifting technique

This paper gives a matching condition for sampled-data critical control systems with persistent and/or transient inputs by using the lifting technique. The obtained condition is given as a set of inequality constraints on the impulse and/or step responses. A computational method for evaluating it is also discussed.     

Stabilisation analysis for switched neutral systems based on sampled-data control

In this paper, the problem of stabilisation analysis for switched neutral systems based on sampled-data control and average dwell time approach is investigated. Delay-dependent stabilisation results are derived in terms of linear matrix inequalities by constructing piecewise Lyapunov–Krasovskii functional based on the Wirtinger's inequality. Also, the controller gain matrix is designed by applying an input-delay approach. Further convex combination technique and some integral inequalities are used to derive less conservative results. The effectiveness of the derived results is validated through numerical examples.     

Design and stabilization of sampled-data neural-network-based control systems.

This paper presents the design and stability analysis of a sampled-data neural-network-based control system. A continuous-time nonlinear plant and a sampled-data three-layer fully connected feedforward neural-network-based controller are connected in a closed loop to perform the control task. Stability conditions will be derived to guarantee the closed-loop system stability. Linear-matrix-inequality- and genetic-algorithm-based approaches will be employed to obtain the largest sampling period and the connection weights of the neural network subject to the considerations of the system stability and performance. An application example will be given to illustrate the design procedure and effectiveness of the proposed approach.     

Adaptive sampled-data based linear quadratic optimal control of stochastic systems

The problem of sampled-data (SD) based adaptive linear quadratic (LQ) optimal control is considered for linear stochastic continuous-time systems with unknown parameters and disturbances. To overcome the difficulties caused by the unknown parameters and incompleteness of the state information, and to probe into the influence of sample size on system performance, a cost-biased parameter estimator and an adaptive control design method are presented. Under the assumption that the unknown parameter belongs to a known finite set, some sufficient conditions ensuring the convergence of the parameter estimate are obtained. It is shown that when the sample step size is small, the SD-based adaptive control is LQ optimal for the corresponding discretized system, and sub-optimal compared with that of the case where the parameter is known and the information is complete.     

Dissipative based adaptive reliable sampled-data control of time-varying delay systems

This paper is concerned with the problem of dissipative based adaptive reliable controller for a class of time delay systems subject to actuator failures and time-varying sampling with a known upper bound on the sampling intervals. By constructing a proper Lyapunov-Krasovskii functional which fully uses the available information about the actual sampling pattern and time delays, a new set of sufficient conditions is derived to obtain the required result. Then, a dissipative based adaptive sampled-data controller is designed such that the resulting closed-loop system is reliable in the sense that it is asymptotically stable and has the prescribed dissipative performance under given constraints. The existence condition of the desired dissipative based adaptive reliable sampled-data controller is obtained in terms of linear matrix inequalities. Further, the performance of the proposed controller is implemented on a liquid propellant rocket motor with a pressure feeding system model. The simulation results show the effectiveness and better performance of the proposed adaptive reliable sampled-data controller over conventional reliable controller.     

Output-feedback control of LPV sampled-data systems

In this paper, we address the analysis and the output-feedback synthesis problems for linear parameter-varying (LPV) sampled-data control systems with potentially variable sampling rates. We assume that the state-space matrices of the plant and the sampling interval depend on parameters that are measurable in real-time and vary in a compact set with bounded variation rates. We explore criteria such as the stability, the energy-to-energy gain (induced L 2 norm) and the energy-to-peak gain (induced L 2 -to- L X norm) of such sampled-data LPV systems using parameter-dependent Lyapunov functions. Based on these analysis results, the corresponding sampled-data output-feedback control synthesis problems are examined. Both analysis and synthesis conditions are formulated in terms of linear matrix inequalities (LMIs) that can be solved via efficient interior-point algorithms.     

Multirate sampled-data control of two-time-scale systems

Two-time-scale decoupling is adopted to obtain slow and fast subsystems. Based on these subsystems, a multirate composite control strategy is derived. It is shown how a recently presented multirate scheme can be modified to handle slow, nonzero mean disturbances, by introducing time incremental models. The improvements with the given multirate control law are illustrated by an example     

Non-uniform sampled-data control of MIMO systems

In this paper, the problem of controlling MIMO plants where the pattern of measurements sampling and control actions delivering is not regular is tackled. Multirate control, time delay systems, missing data environments as well as limited computing and communication resources are on the grounds of these problems. There is an extensive literature on these topics. Different models are reviewed and, from the control viewpoint, model-based control design techniques are reported and new algorithms are proposed. Among the main challenges are the achievement of good performance and the avoidance of intersampling ripple. Both issues are considered and some results are discussed.     

Continuous-time deadbeat control for sampled-data systems

In this paper, the continuous-time deadbeat control problem for the sampled-data systems is considered. We derived the class of all controllers that achieve the continuous-time deadbeat control     

Ripple-free deadbeat control for sampled-data systems

In this paper the ripple-free deadbeat control problem for sampled-data systems is considered. This control objective is to settle the error to zero for all time after some finite settling time, in other words to eliminate the ripples between the sampling instants in deadbeat control of sampled-data systems. The necessary and sufficient conditions to solve this problem are derived and related to the system type, and a method of constructing the ripple-free deadbeat control system is presented.     

Delay-dependent sampled-data control based on delay estimates

In this paper the sampled-data stabilization of linear time-invariant systems with feedback delay is considered. We assume that the delay is time-varying and that its value is approximatively known. We investigate how to use the available information about the evolution of delays for adapting the control law in real time. Numerical methods for the design of a delay-dependent controller are presented. This allows for providing a control for some cases in which the stabilization cannot be ensured using a controller with a fixed structure.     

Some qualitative properties of sampled-data control systems

The authors consider sampled-data control systems which consist of an interconnection of a continuous-time nonlinear plant and a digital controller which has quantizers (but is otherwise linear), along with the required interface elements (A/D and D/A converters). In the present paper the authors study the qualitative effects of the quantizers and the plant nonlinearities of these systems     

Optimal control of sampled-data piecewise affine systems

This paper discusses the optimal continuous-time control problem of a class of piecewise affine (PWA) systems, where the switching action of the discrete state is determined at each sampling time according to a condition on the continuous state. Such a system is called here the sampled-data PWA (SD-PWA) system. First, important remarks on the control design of this system via the continuous-(or discrete-)time PWA model are pointed out, which motivate us to use the SD-PWA model. Next, based on the good properties of the proposed model, an optimal continuous-time controller of the SD-PWA systems is proposed.     

Stabilization of nonlinear systems using sampled-data output-feedback fuzzy controller based on polynomial-fuzzy-model-based control approach

This paper investigates the stability of sampled-data output-feedback (SDOF) polynomial-fuzzy-model-based control systems. Representing the nonlinear plant using a polynomial fuzzy model, an SDOF fuzzy controller is proposed to perform the control process using the system output information. As only the system output is available for feedback compensation, it is more challenging for the controller design and system analysis compared to the full-state-feedback case. Furthermore, because of the sampling activity, the control signal is kept constant by the zero-order hold during the sampling period, which complicates the system dynamics and makes the stability analysis more difficult. In this paper, two cases of SDOF fuzzy controllers, which either share the same number of fuzzy rules or not, are considered. The system stability is investigated based on the Lyapunov stability theory using the sum-of-squares (SOS) approach. SOS-based stability conditions are obtained to guarantee the system stability and synthesize the SDOF fuzzy controller. Simulation examples are given to demonstrate the merits of the proposed SDOF fuzzy control approach.     

Discrete-time modeling of sampled-data control systems with directfeedthrough

Discrete-time models of sampled-data control systems are addressed when both a continuous-time plant and a discrete-time controller have a feedthrough. It is pointed out that in this case discrete-time models which can be found in most references should not be used in the closed-loop context. A new state-space model appropriate for the closed-loop modeling and formulas for calculating the related discrete-time pulse transfer functions are derived. Intersample phenomena are studied and the feasibility of that model to describe systems with parasitic dynamics is emphasized. Examples from the literature illustrate the relevance of the issue     

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.     

Block multirate input-output model for sampled-data control systems

A model for multirate sampled-data systems is presented. A detailed analysis of nonconventional sampled-data control systems (SDCS) is performed. The block multirate input-output model illustrates the control possibilities of multirate SDCS. It is obtained from either a transfer function matrix or a state variable representation. The model provides a direct way to represent, design, and understand either periodic or predictive controllers. A controller design methodology suitable for multivariable, multirate, nonsynchronous SDCS is also presented. The main feature is the freedom to achieve important objectives such as structure assignment, decoupling, and desired transient behavior, as well as reference matching, optimal control, or disturbance rejection