Dynamic output feedback control for CPSs under transmission delays and sparse malicious attacks

This paper is concerned with analyzing a novel model transformation of discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and applying it to dynamic output feedback (DOF) controller design. A new auxiliary model is proposed by employing a new approximation for time-varying delay state, and then delay partitioning method is used to analyze the scaled small gain of this auxiliary model. A sufficient condition on discrete-time T-S fuzzy systems with time-varying delays, which guarantees the corresponding closed-loop system to be asymptotically stable and has an induced l 2 disturbance attenuation performance, is derived by employing the scaled small gain theorem. Then the solvability condition for the induced l 2 DOF control is also established, by which the DOF controller can be found by solving a set of linear matrix inequalities (LMIs).

In terminal guidance phase, only partial information concerning the interception geometry is available. To intercept a target in specified direction under this condition, an impact angle constrained guidance law is proposed based on the dynamic output feedback. The guidance law doesn't use the rate of line-of-sight angle, and can guarantee convergence speed of the closed-loop system. Utilizing the parametric algebraic Riccati equation, a dynamic output feedback controller is designed. The controller contains a feedback law and an observer is obtained. Through integrated design of the parameters of the feedback law and the observer, the closed-loop system can be transformed to a new system, whose system matrix is a Jordan matrix. Using Lyapunov approach, desired convergence speed of the new system can be obtained by tuning its poles. And the same convergence speed of the original closed-loop system can also be achieved. Based on the dynamic output feedback controller, an impact angle constrained guidance law is derived. The guidance law is demonstrated by numerical simulation. Convergence speed can be guaranteed by the guidance law, and high guidance precision is achieved.

This paper considers the design problem of dynamic output feedback control for fractional-order (FO) Takagi-Sugeno fuzzy systems with uncertain parameters. Via the application of FO system stability theory, robust control method and the linear matrix inequality techniques, sufficient conditions are given for the stability analysis and the existence of the dynamic fuzzy output feedback controllers. The dynamic output feedback controller designed here guarantees the robust stability of the closed-loop system. Finally, a fractional order chaotic system simulation example is given to illustrate the effectiveness of the design approach here.

The problem of robust stabilisation is considered for uncertain systems using linear static output feedback (SOF) controllers and linear dynamical output feedback (DOF) controllers with fixed order. The existence conditions of output feedback controllers are given by matrix inequalities and result in some nonlinear optimisation problems. A class of uncertain plants whose nominal systems are minimal phase with a full row rank can be robustly stabilised by an SOF controller and DOF controller with any order, and controllers can be obtained by solving some linear matrix inequalities (LMIs). The method is demonstrated by two numerical examples

In this work, we develop a method for dynamic output feedback covariance control of the state covariance of linear dissipative stochastic partial differential equations (PDEs) using spatially distributed control actuation and sensing with noise. Such stochastic PDEs arise naturally in the modeling of surface height profile evolution in thin film growth and sputtering processes. We begin with the formulation of the stochastic PDE into a system of infinite stochastic ordinary differential equations (ODEs) by using modal decomposition. A finite-dimensional approximation is then obtained to capture the dominant mode contribution to the surface roughness profile (i.e., the covariance of the surface height profile). Subsequently, a state feedback controller and a Kalman-Bucy filter are designed on the basis of the finite-dimensional approximation. The dynamic output feedback covariance controller is subsequently obtained by combining the state feedback controller and the state estimator. The steady-state expected surface covariance under the dynamic output feedback controller is then estimated on the basis of the closed-loop finite-dimensional system. An analysis is performed to obtain a theoretical estimate of the expected surface covariance of the closed-loop infinite-dimensional system. Applications of the linear dynamic output feedback controller to the linearized stochastic Kuramoto-Sivashinsky equation are presented.

In this paper, a new stabilization condition of switched fuzzy systems is proposed. The dynamic output feedback control problem is addressed for a class of switched fuzzy Systems. The dynamic output feedback with sufficient conditions and the design method of controller is given using multiple Lyapunov function method and switching law. The closed-loop system asymptotically stable is given by the designed controller. Adopting the dynamic output feedback control law, the order of the closed-loop system is reduced, which is helpful to improve the reliability of the system. Finally, simulation results verify the effectiveness of the conclusion.

For nonlinear space-varying parabolic partial differential equation systems (PPDESs) with random time-varying delay, this article introduces a dynamic fuzzy boundary output feedback (DFBOF) control under noncollocated boundary measurement (NCBM). Initially, the nonlinear delayed PPDESs are represented by Takagi–Sugeno (T–S) fuzzy models and random time-varying delay is considered by taking the influence of uncertain factors, which belongs to two intervals in a probabilistic way. Since the system state is not fully available and NCBM makes the boundary control design very difficult, a fuzzy observer under NCBM is presented to surmount the design difficulty. Subsequently, an observer-based fuzzy boundary controller is proposed and spatial linear matrix inequality (SLMI)-based sufficient conditions to ensure mean-square exponential stability are obtained for closed-loop delayed PPDESs by utilizing the Lyapunov direct method and Wirtinger inequality. Then, to solve the SLMIs, the feasibility conditions of DFBOF controller design for nonlinear delayed PPDES are expressed in LMIs. Finally, two examples are offered to demonstrate the validity of the presented dynamic fuzzy boundary control approach.

For quasi-linear parameter varying (quasi-LPV) systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR) example is given to illustrate the effectiveness of the approach.

The problem of dynamic output feedback control stabilization is considered for a class of multi-time delays uncertain nonlinear systems. Based on LMI and proper Lyapunov functions, a sufficient condition for the existence of robust output feedback controller is proposed, which ensures that the closed-loop system is robust stable. The dynamic output feedback controller is designed by the feasible solution of the matrix inequality with constraint. At last, by using matrix orthogonal complement, the parameters solving methods of output feedback controller is also provided.

The goal of this paper is to describe an active decentralized fault-tolerant control (ADFTC) strategy based on dynamic output feedback for reconfigurable manipulators with concurrent actuator and sensor failures. Consider each joint module of the reconfigurable manipulator as a subsystem, and treat the fault as the unknown input of the subsystem. Firstly, by virtue of linear matrix inequality (LMI) technique, the decentralized proportional-integral observer (DPIO) is designed to estimate and compensate the sensor fault online; hereafter, the compensated system model could be derived. Then, the actuator fault is estimated similarly by another DPIO using LMI as well, and the sufficient condition of the existence ofH∞fault-tolerant controller in the dynamic output feedback is presented for the compensated system model. Furthermore, the dynamic output feedback controller is presented based on the estimation of actuator fault to realize active fault-tolerant control. Finally, two 3-DOF reconfigurable manipulators with different configurations are employed to verify the effectiveness of the proposed scheme in simulation. The main advantages of the proposed scheme lie in that it can handle the concurrent faults act on the actuator and sensor on the same joint module, as well as there is no requirement of fault detection and isolation process; moreover, it is more feasible to the modularity of the reconfigurable manipulator.

This paper discusses the problems of the finite-time annular domain stability (FTAD-stability) and stabilization of discrete-time stochastic systems (DTSS). First, a definition of FTAD-stability for DTSS is given and a stability criterion is also proposed. Second, we respectively give some sufficient conditions for the existence of state feedback controller (SFC), static output feedback controller (SOFC) and dynamic output feedback controller (DOFC). Finally, a numerical example is utilized to show the effectiveness of proposed method.

This work presents a convex parametrization of H ∞ output feedback controllers for positively dominated systems. The objective is to design static and dynamic output feedback controllers such that the closed-loop system is positively dominated, asymptotically stable and the H ∞ norm from the exogenous input to the regulated output is minimized. By utilizing Youla parametrization, the stabilizing controllers which give rise to a positively dominated system is parameterized by Q-parameters and extended to design static and dynamic H ∞ output feedback controllers through semi-definite programming (SDP). Due to the versatility of the presented framework for positively dominate systems, the design is extended to robust performance scenarios with structured and unstructured norm-bounded uncertainties.

Magnetorheological fluid (MRF) dampers have been utilized in semi-active air suspension (SAAS) due to their attractive advantages. This paper investigates a novel robust fuzzy output feedback controller for semi-active air suspension with MRF damper (SAAS-MRFD), considering time delay and actuator saturation. An aero-thermodynamics theory is first utilized to describe the nonlinear air spring. The damping force of the MRF damper is represented by a hyperbolic tangent model. The interval type-2 (IT-2) Takagi–Sugeno (T-S) fuzzy method is second employed to capture those nonlinearities of the air spring and MRF damper. Considering the difficulty to measure all states, a novel dynamic output feedback (DOF) controller is developed by an appropriate Lyapunov–Krasovskii function and the reciprocally convex technique with consideration of time delay, actuator saturation, and output constraints. The effectiveness of the proposed controller is validated by both simulation and a quarter-car test rig (QCTR). The results indicate that the proposed controller has better performance in vibration reduction than the recent similar controllers in the literature.

Robust output regulation of discrete-time linear systems by quantized output feedback control

The dynamic output feedback L2 disturbance attenuation control of linear parameter-varying (LPV) singular systems is investigated in this paper. Based on a general Lyapunovine quality, we first provide a condition that guaranteesthe admissability and the L2 gain performance of LPV singular systems. Then, the existence of dynamic output feedback L2 disturbance attenuation controller of the system is discussed. Finally, a dynamic output feedback controller is constructed by solving a coupled generalized algebraic Riccati inequalities. It is shown that the closed loop system is admissible and satisfies the desired L2 performance.