Da-Wei Ding

Bio: Da-Wei Ding is an academic researcher from University of Science and Technology Beijing. The author has contributed to research in topics: Linear system & Discrete time and continuous time. The author has an hindex of 18, co-authored 94 publications receiving 1169 citations. Previous affiliations of Da-Wei Ding include Northeastern University & Northeastern University (China).

Control Synthesis of Discrete-Time T–S Fuzzy Systems Based on a Novel Non-PDC Control Scheme

Abstract: This paper proposes relaxed stabilization conditions of discrete-time nonlinear systems in the Takagi-Sugeno (T-S) fuzzy form. By using the algebraic property of fuzzy membership functions, a novel nonparallel distributed compensation (non-PDC) control scheme is proposed based on a new class of fuzzy Lyapunov functions. Thus, relaxed stabilization conditions for the underlying closed-loop fuzzy system are developed by applying a new slack variable technique. In particular, some existing fuzzy Lyapunov functions and non-PDC control schemes are special cases of the new Lyapunov function and fuzzy control scheme, respectively. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.

Fuzzy Filter Design for Nonlinear Systems in Finite-Frequency Domain

Abstract: This paper is concerned with the problem of fuzzy-filter design for discrete-time nonlinear systems in the Takagi-Sugeno (T-S) form. Different from existing fuzzy filters, the proposed ones are designed in finite-frequency domain. First, a so-called finite-frequency l2 gain is defined that extends the standard l2 gain. Then, a sufficient condition for the filtering-error system with a finite-frequency l2 gain is derived. Based on the obtained condition, three fuzzy filters are designed to deal with noises in the low-, middle-, and high-frequency domain, respectively. The proposed fuzzy-filtering method can get a better noise-attenuation performance when frequency ranges of noises are known beforehand. An example about a tunnel-diode circuit is given to illustrate its effectiveness.

H ∞ static output feedback control for discrete-time switched linear systems with average dwell time

Abstract: This study investigates the problem of H∞ static output feedback (SOF) control for discrete-time switched linear systems with average dwell time. By the aid of multiple Lyapunov functions combined with Finsler's lemma, a switched SOF controller is designed such that the closed-loop switched system is exponentially stable and achieves a weighted L2-gain. Sufficient conditions for SOF control are derived and formulated in terms of linear matrix inequalities (LMIs). The minimal average dwell time and the corresponding SOF controller are obtained from the LMI conditions for a given system decay degree. The proposed method is less conservative than the existing ones, which is validated by a numerical example.

Chaos and Hopf bifurcation control in a fractional-order memristor-based chaotic system with time delay

Abstract: In this paper, a time-delayed feedback controller is proposed in order to control chaos and Hopf bifurcation in a fractional-order memristor-based chaotic system with time delay. The associated characteristic equation is established by regarding the time delay as a bifurcation parameter. A set of conditions which ensure the existence of the Hopf bifurcation are gained by analyzing the corresponding characteristic equation. Then, we discuss the influence of feedback gain on the critical value of fractional order and time delay in the controlled system. Theoretical analysis shows that the controller is effective in delaying the Hopf bifurcation critical value via decreasing the feedback gain. Finally, some numerical simulations are presented to prove the validity of our theoretical analysis and confirm that the time-delayed feedback controller is valid in controlling chaos and Hopf bifurcation in the fractional-order memristor-based system.

Fuzzy Adaptive Actuator Failure Compensation Control of Uncertain Stochastic Nonlinear Systems With Unmodeled Dynamics

Abstract: This paper investigates fuzzy adaptive actuator failure compensation control for a class of uncertain stochastic nonlinear systems in strict-feedback form. These stochastic nonlinear systems contain the actuator faults of both loss of effectiveness and lock-in-place, unmodeled dynamics, and without direct measurements of state variables. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is established to estimate the unmeasured states. By introducing the dynamical signal and the changing supply function technique design into the backstepping control design, a robust adaptive fuzzy fault-tolerant control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are bounded in probability in the presence of the actuator failures and the unmodeled dynamics. Simulation results are provided to show the effectiveness of the control approach.

The Fourth Element.

Abstract: This tutorial clarifies the axiomatic definition of (v(α); i(β)) circuit elements via a lookup table dubbed an A-pad, of admissible (v; i) signals measured via Gedanken probing circuits. The (v(α); i(β)) elements are ordered via a complexity metric. Under this metric, the memristor emerges naturally as the fourth element, characterized by a state-dependent Ohm's law. A logical generalization to memristive devices reveals a common fingerprint consisting of a dense continuum of pinched hysteresis loops whose area decreases with the frequency ω and tends to a straight line as ω ~ ∞, for all bipolar periodic signals and for all initial conditions. This common fingerprint suggests that the term memristor be used hence-forth as a moniker for memristive devices.

Control Synthesis of Discrete-Time T–S Fuzzy Systems via a Multi-Instant Homogenous Polynomial Approach

Abstract: This paper deals with the problem of control synthesis of discrete-time Takagi–Sugeno fuzzy systems by employing a novel multiinstant homogenous polynomial approach. A new multiinstant fuzzy control scheme and a new class of fuzzy Lyapunov functions, which are homogenous polynomially parameter-dependent on both the current-time normalized fuzzy weighting functions and the past-time normalized fuzzy weighting functions, are proposed for implementing the object of relaxed control synthesis. Then, relaxed stabilization conditions are derived with less conservatism than existing ones. Furthermore, the relaxation quality of obtained stabilization conditions is further ameliorated by developing an efficient slack variable approach, which presents a multipolynomial dependence on the normalized fuzzy weighting functions at the current and past instants of time. Two simulation examples are given to demonstrate the effectiveness and benefits of the results developed in this paper.

Active Steering Actuator Fault Detection for an Automatically-Steered Electric Ground Vehicle

Abstract: In this paper, we investigate the actuator fault detector design problem for an electric ground vehicle (EGV) that is equipped with an active front-wheel steering system. Since the EGV can be steered by a motor automatically, it is desired to design a fault detector for the steering actuator for safety reasons. A two degree of freedom lateral nonlinear vehicle model is established. The nonlinear vehicle model is converted to a linear-parameter-varying (LPV) form and the scheduling vector is related to the vehicle longitudinal velocity. Since it is not easy to measure the longitudinal velocity precisely, the uncertain measurement on the longitudinal velocity is considered and the weighting factors of LPV submodels are subject to uncertainties. Based on the uncertain LPV model, a gain-scheduling fault detector is proposed and an augmented system is obtained. The desired steering angle and the faulty steering angle are both involved in the augmented system. As the steering angle generally has a low-frequency working range, the steering angle amplitude spectrums of three different maneuvers are studied, and the frequency working range is determined. The stability, the $\mathcal {H}{\_}$ performance, and the $\mathcal {H}_{\infty }$ performance of the augmented system are all exploited. Based on the analysis results, the mixed $\mathcal {H}{\_}$ / $\mathcal {H}_{\infty }$ fault detector design method is developed. An experimental test is used to show the performance of the designed fault detector.

Observer-Based Neuro-Adaptive Optimized Control of Strict-Feedback Nonlinear Systems With State Constraints

Abstract: This article proposes an adaptive neural network (NN) output feedback optimized control design for a class of strict-feedback nonlinear systems that contain unknown internal dynamics and the states that are immeasurable and constrained within some predefined compact sets. NNs are used to approximate the unknown internal dynamics, and an adaptive NN state observer is developed to estimate the immeasurable states. By constructing a barrier type of optimal cost functions for subsystems and employing an observer and the actor-critic architecture, the virtual and actual optimal controllers are developed under the framework of backstepping technique. In addition to ensuring the boundedness of all closed-loop signals, the proposed strategy can also guarantee that system states are confined within some preselected compact sets all the time. This is achieved by means of barrier Lyapunov functions which have been successfully applied to various kinds of nonlinear systems such as strict-feedback and pure-feedback dynamics. Besides, our developed optimal controller requires less conditions on system dynamics than some existing approaches concerning optimal control. The effectiveness of the proposed optimal control approach is eventually validated by numerical as well as practical examples.