Jianxing Liu

Extended State Observer-Based Sliding-Mode Control for Three-Phase Power Converters

This paper proposes an extended state observer (ESO) based second-order sliding-mode (SOSM) control for three-phase two-level grid-connected power converters. The proposed control technique forces the input currents to track the desired values, which can indirectly regulate the output voltage while achieving a user-defined power factor. The presented approach has two control loops. A current control loop based on an SOSM and a dc-link voltage regulation loop which consists of an ESO plus SOSM. In this work, the load connected to the dc-link capacitor is considered as an external disturbance. An ESO is used to asymptotically reject this external disturbance. Therefore, its design is considered in the control law derivation to achieve a high performance. Theoretical analysis is given to show the closed-loop behavior of the proposed controller and experimental results are presented to validate the control algorithm under a real power converter prototype.

Robust Model-Based Fault Diagnosis for PEM Fuel Cell Air-Feed System

In this paper, the design of a nonlinear observer-based fault diagnosis approach for polymer electrolyte membrane (PEM) fuel cell air-feed systems is presented, taking into account a fault scenario of sudden air leak in the air supply manifold. Based on a simplified nonlinear model proposed in the literature, a modified super-twisting (ST) sliding mode algorithm is employed to the observer design. The proposed ST observer can estimate not only the system states, but also the fault signal. Then, the residual signal is computed online from comparisons between the oxygen excess ratio obtained from the system model and the observer system, respectively. Equivalent output error injection using the residual signal is able to reconstruct the fault signal, which is critical in both fuel cell control design and fault detection. Finally, the proposed observer-based fault diagnosis approach is implemented on the MATLAB/Simulink environment in order to verify its effectiveness and robustness in the presence of load variation.

Event-triggered sliding mode control of stochastic systems via output feedback ☆

Abstract This paper is concerned with event-triggered sliding mode control (SMC) for uncertain stochastic systems subject to limited communication capacity. We consider the stochastic perturbation, exogenous disturbance and the network-induced communication constraints in a whole framework of SMC design. The measurable output is adequately sampled for periodic computation of a designed event trigger. Network-induced delays are characterized in the transmission over a shared network communication from sensor to controller. An event-triggered zero-order-hold (ZOH) is employed to keep receiving and sending the delayed measurement for control updating, and a state observer is designed to estimate the system state and to facilitate the design of sliding surface. Then, based on the measurement and observer’s outputs, a novel SMC law is presented. The stochastic stability for the overall closed-loop system is analyzed, and the exogenous disturbance is attenuated in an H ∞ sense. Furthermore, the presented event-triggered SMC methods are successfully applied to multi-loop control case considering shared communication limitation. Simulation results are provided to verify the effectiveness of the proposed design scheme.

Reliable Filter Design for Sensor Networks Using Type-2 Fuzzy Framework

This paper studies the problem of reliable filter problem for a category of sensor networks in the framework of interval type-2 fuzzy model. In the filter design, the random link failures, which are caused possibly by missing measurements as well as by probabilistic communication failures, are considered to illustrate more realistic dynamical behaviors of sensor networks. In order to tackle the uncertainties existing in systems, interval type-2 (IT2) fuzzy approach is utilized to establish the model, wherein upper and lower membership functions together with weighting coefficients are employed to express the uncertainties. An distributed IT2 fuzzy filter model is constructed to estimate system states. Using the Lyapunov theory, sufficient conditions have been given to ensure that the filtering error system is mean-square asymptotically stable and satisfies the predefined average

Disturbance Observer-Based Antiwindup Control for Air-Breathing Hypersonic Vehicles

\mathcal {H}_{\infty }

Approximate Back-Stepping Fault-Tolerant Control of the Flexible Air-Breathing Hypersonic Vehicle

performance level. Moreover, the criteria to design the filter parameters are developed through using cone complementary linearization approach. Finally, a practical example is given to validate the proposed method.

Observer-Based Adaptive Fault-Tolerant Tracking Control of Nonlinear Nonstrict-Feedback Systems

In this paper, a combination of feedback linearization and disturbance observer-based control (DOBC) is adopted for the design of a state-feedback controller that regulates the velocity and altitude of air-breathing hypersonic vehicles (AHVs) subject to constrained inputs. First, a disturbance observer is established to estimate the overall effect of possible uncertainties and disturbances on the nominal vehicle model which is called the lumped disturbance. Then, a compensation method is proposed based on disturbance observer and feedback linearization control to counteract the mismatched lumped disturbance. Furthermore, a novel antiwindup modification is implemented on the baseline control to handle the possible input saturation. The designed controller addresses the issue of stability robustness with respect to system uncertainties and disturbances, and achieves zero-error tracking with good performance and antiwindup property meanwhile, which is the major merit compared with other existing AHV controllers. Finally, simulation is presented to verify the effectiveness of this control scheme.

Adaptive Fuzzy Control for Nonlinear Networked Control Systems

This paper deals with fault-tolerant output tracking control for the flexible air-breathing hypersonic vehicle (AHV) subject to parametric uncertainties, external disturbances, and actuator constraints. By regarding the flexible dynamics as equivalent disturbances, the vehicle model can be split into three functional subsystems, namely, horizontal translation subsystem, vertical translation subsystem, and rotation subsystem. Then, for each subsystem, a disturbance observer is utilized to estimate the lumped effect of model uncertainties, external disturbances, and actuator faults, while a novel auxiliary system combined with the command prefilter is constructed to handle the physical constraints on actuators. Furthermore, sliding mode control is employed to design control commands for the three subsystems, sequentially. The proposed controller modifies the reference trajectories dynamically when one or more actuators become constrained, and can steer the AHV to the desired trim finally. Simulation results are provided to demonstrate the effectiveness of the designed controller.

Design and Optimization of Interval Type-2 Fuzzy Logic Controller for Delta Parallel Robot Trajectory Control

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of “explosion of complexity”. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper.

A Novel Adaptive Neural Network Constrained Control for a Multi-Area Interconnected Power System With Hybrid Energy Storage

This paper studies the problem of adaptive fuzzy control for a category of single-input single-output nonlinear networked control systems with network-induced delay and data loss based on adaptive backstepping control approach. Fuzzy logic systems are used to approximate the unknown nonlinear characteristics existing in the system, while Pade approximation is introduced to handle network-induced delay. Data loss occurs intermittently and stochastically in the data transmitting process, which is regarded as the delay in the controller design. In the framework of adaptive fuzzy backstepping technique, a novel state-feedback adaptive controller is constructed to ensure all signals in the resulting closed-loop system to be bounded and the state variables can be regulated to the origin. Finally, two examples are given to show the validity of the proposed results.