A Novel Disturbance Observer Based Fixed-Time Sliding Mode Control for Robotic Manipulators With Global Fast Convergence

This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators.First,a fixed-time disturbance observer(FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems.Then an adaptive scheme is used and the adaptive FTDO(AFTDO) is developed,so that the priori knowledge of the lumped disturbance is not required.Further,a new non-singular fast terminal sliding mode(NFTSM) surface is designed by using an arctan function,which helps to overcome the singularity problem and enhance the robustness of the system.Based on the estimation of the lumped disturbance by the AFTDO,a fixed-time non-singular fast terminal sliding mode controller(FTNFTSMC)is developed to guarantee the trajectory tracking errors converge to zero within a fixed time.The settling time is independent of the initial state of the system.In addition,the stability of the AFTDO and FTNFTSMC is strictly proved by using Lyapunov method.Finally,the fixed-time NFESM(FTNFTSM) algorithm is validated on a 2-link manipulator and comparisons with other existing sliding mode controllers(SMCs) are performed.The comparative results confirm that the FTNFTSMC has superior control performance.

Fuzzy-Model-Based Finite Frequency Fault Detection Filtering Design for Two-Dimensional Nonlinear Systems

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy models.Firstly,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to faults.It has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design approach.Then,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the threshold.Finally,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

Policy Gradient Adaptive Dynamic Programming for Model-Free Multi-Objective Optimal Control

Dear Editor,In this letter,the multi-objective optimal control problem of nonlinear discrete-time systems is investigated.A data-driven policy gradient algorithm is proposed in which the action-state value function is used to evaluate the policy.In the policy improvement process,the policy gradient based method is employed.

Distributed Dimensionality Reduction Filtering for CPSs Under DoS Attacks

Dear Editor,This letter concerns about the distributed dimensionally reduction filtering for a class of cyber physical systems with denial of service(DoS)attacks.Considering each sensor exchanging measurements with neighbors subjected to finite network energy,the dimensionally reduction method is applied.

Optimal Injection Attack for UCPS Under Vertical Depth-Keeping Task Via Game Approach

Dear Editor, This letter concerns about the security problem of underwater cyber-physical system(UCPS) for depth-keeping task in the vertical plane. A dynamic parametric model of the UCPS with ocean currents and hydrostatic is considered. With the intelligence of the controller, the objective function of a zero-sum game between the attacker and the controller is introduced. The attacker destroys the depth-keeping task of UCPS by injecting the designed false data into the system.

Event-triggered adaptive finite-time control for nonlinear systems under asymmetric time-varying state constraints

This paper investigates the issue of event-triggered adaptive finite-time state-constrained control for multi-input multi-output uncertain nonlinear systems.To prevent asymmetric time-varying state constraints from being violated,a tan-type nonlinear mapping is established to transform the considered system into an equivalent“non-constrained”system.By employing a smooth switch function in the virtual control signals,the singularity in the traditional finite-time dynamic surface control can be avoided.Fuzzy logic systems are used to compensate for the unknown functions.A suitable event-triggering rule is introduced to determine when to transmit the control laws.Through Lyapunov analysis,the closed-loop system is proved to be semi-globally practical finite-time stable,and the state constraints are never violated.Simulations are provided to evaluate the effectiveness of the proposed approach.