Robust Finite-Time Output Feedback $$ H_\infty $$ H ∞ Control for Stochastic Jump Systems with Incomplete Transition Rates

Semi-global finite-time output feedback stabilization for a class of large-scale uncertain nonlinear systems

Quantized output feedback control for nonlinear Markovian jump distributed parameter systems with unreliable communication links

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.

this paper investigates the problem of robust gain-scheduled static output feedback (SOF) controller for a class of uncertain linear parameter varying systems (LPVSs). An uncertain LPVS is described by an interconnection of a nominal LPVS which is solely dependent on the measurable parameters, and a block structured uncertainty. For designing a H∞ gain-scheduled SOF controller as well as performing the stability analysis, the proposed method uses integral quadratic constraints (IQCs) to derive the linear matrix inequalities (LMIs) without any constraints on nominal system matrices. The performance and effectiveness of the proposed method are demonstrated based on an example.

Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systemsIn this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.

In view of the marine surface vehicles are subject to unknown time-varying external disturbance and its velocities are not available for feedback, a robust finite-time output feedback control scheme is presented for multiple marine surface vehicles to achieve precise formation control in this paper. Without neglecting the first time derivative of disturbance, a novel finite-time extended state observer (FTESO) is proposed to precisely estimate the external disturbance and velocity information in finite time. Based on the outputs of FTESO, the distributed formation controller is designed to guarantee that a group of marine surface vehicles can track the time-varying virtual leader in finite time with precise tracking performance. The errors of the proposed FTESO and formation controller can be guaranteed to converge to zero in finite time by using the homogeneous method and the Lyapunov theory. Numerical simulations are presented to illustrate the effectiveness of the proposed finite-time output feedback formation control scheme.

This paper deals with the problem of robust fault-tolerant dynamic output feedback controllers design for time-delay systems. The system under consideration involves parameter uncertainties and time-delay. The purpose is to design the dynamic output feedback controller such that, for all admissible uncertainties as well as actuator failures, the system remains stable. The sufficient condition is given in the form of linear matrix inequalities (LMIs) to maintain the stability of the closed-loop system for the time-delay system against actuator failures, and the design of the dynamic output feedback controller is proposed. Finally, an illustrative example and simulation results are given to demonstrate the effectiveness of the proposed method.

A robust dynamic output feedback controller synthesis algorithm considering H∞/H2performance and regional pole placement is addressed for a nonlinear system with parameter uncertainties and external disturbance. First, the formulation of a gain‐scheduled mixed‐objective robust dynamic output feedback controller for continuous‐time polytopic linear parameter varying (LPV) systems is presented. To reduce conservativeness, some auxiliary slack variables and parameter‐dependent Lyapunov functions are employed in addition to well‐established performance conditions. Then, sufficient conditions for the desired gain‐scheduled mixed‐objective robust dynamic output feedback controllers are cast into an efficiently tractable finite‐dimensional convex optimization problem in terms of linear matrix inequalities (LMIs). Finally, numerical simulation shows the validity of the proposed controller, which has good stability, strong robustness, satisfied disturbance attenuation ability, and smooth dynamic properties.

In this paper, a robust output feedback stabilization for a class of Autonomous Underwater Vehicle (AUV) is investigated. Two cases for, nonlinear, decoupled equations of motion of AUV in steering plane are considered in this work. In the first scenario, where all states are measurable, semi-global asymptotic stability for a class of AUV is shown by proposing a state-feedback controller based on Sliding Mode Control (SMC). The stability analysis is evaluated under model uncertainties and parametric variations. Then for the second case, Extended High-Gain Observer (EHGO), augmented with Extended Kalman Filter (EKF) is used to estimate the immeasurable states. It is shown that the states of the closed-loop system with output feedback controller, approach the invariant manifold in finite time and stay there. Efficacy of the proposed controllers is demonstrated with the help of numerical simulations.

Markovian jumping systems have arisen naturally in the mathematical modeling of phenomena spanning disciplines in the social sciences, natural sciences, and engineering. This kind of stochastic dynamical systems can be employed to model the dynamics when parameters are subject to random abrupt changes due to sudden environment changes, subsystem switching, system noises, executor faults, and so forth. Much attention has been given to modeling, optimization, and real applications of such stochastic dynamical systems in the literature in recent years. As the advanced control and optimization will provide a basis for the design and application of such stochastic systems, these advanced techniques would result in substantial and sustainable benefits. The accepted papers in this special issue include stochastic stability, stabilization, stochastic control optimization, system modeling and identification methods, predictive control, signal processing, robust filtering, multiagent systems, networked control systems, time-delayed systems, neural networks, the Takagi-Sugeno fuzzy systems, simulated annealing, and fault detection methods.

Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF) network that can determine its structure dynamically to approximate unknown system dynamics. Radial basis functions are added or removed online in order to achieve the desired tracking accuracy and prevent to network redundancy. The raised-cosine RBF is employed to enable fast and efficient training and output evaluation of the RBF network. The direct adaptive robust output feedback controller is constructed by utilizing a high-gain observer to estimate the tracking error for the controller implementation. The closed-loop systems driven by the variable neural direct adaptive robust controllers are actually switched systems.

This note investigates the problem of output feedback H∞ control for linear discrete-time systems. Three types of H∞ controllers are considered, namely, static output feedback controllers, dynamic output feedback controllers, and observer-based output feedback controllers. New design conditions for the three type of output feedback controllers are introduced in terms of unified linear matrix inequality (LMI) representations, which guarantee the prescribed H∞ performances of the closed-loop systems. In contrast to the existing LMI conditions for designing the output feedback H∞ controllers, the improvement of the proposed results over the existing ones is shown by theoretical proof and numerical example.

Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate

This paper investigates the problem of delay-dependent output feedback guaranteed cost controller design for uncertain discrete-time switched systems with time-varying state delay. The uncertainties are assumed to have a structured linear fractional form. The objective is to design a switched dynamic output feedback controller guaranteeing the asymptotic stability of the resulting closed-loop system and minimizing a specified cost function. Based on a delay-dependent switched Lyapunov-Krasovskii functional (DDSLKF) combined with Finsler's Lemma, a novel delay-dependent robust performance analysis result is first proposed and in turn the output feedback controller synthesis is developed. It is shown that the controller parameters can be obtained by solving a set of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and less conservatism of the proposed approach.

This paper studies the robust static output feedback (SOF) problem considering pole placement constraints for linear systems with polytopic uncertainty as well as linear parameter varying (LPV) systems. New linear matrix inequality (LMI) approaches are proposed for the SOF controller design while the pole placement, H2, and H∞ constraints are guaranteed. In addition, the gain-scheduled SOF controller will be designed for LPV systems if system parameters are measured. The proposed methods can be applied to general linear systems without imposing any constraints on system matrices. The performance and effectiveness of the proposed methods are shown using two examples.