Robust Decentralized Adaptive Fuzzy Control of Large‐Scale Nonaffine Nonlinear Systems With Strong Interconnection and Application to Automated Highway Systems

A novel robust terminal sliding-mode control (RTSMC) based on radial basis function (RBF) neural network is proposed firstly for controlling the attitude and position of the quadrotor, guaranteeing the system converged to stability point in a limited time. After establishing the nonlinear kinematics and dynamics models of the system, robust control is adopted in the RBF neural network terminal sliding-mode controller such that the impact of external interference is reduced effectively. Resorting to the Lyapunov function, the asymptotically stable condition for the considered system is obtained, in which the convergence of the system is deduced in a finite time. Furthermore, simulation results are given to show the faster convergence speed and strong robustness for the considered system with RBF and RTSMC. Finally, the effectiveness and robustness of the developed control strategy is validated experimentally.

Section: Introductionmentioning

confidence: 99%

Neural‐network‐based robust terminal sliding‐mode control of quadrotor

Lin

Wang

Liu

2020

“…In the application aspect, [5] proposed a current sharing control algorithm for parallel DC‐DC buck converters based on finite‐time control. The decentralized control approach has also been applied to hydrostatic wind turbine drivetrain [6], longitudinal vehicular platoons with non‐uniform communication topology [7] and automated highway systems [8]. However, the aforementioned decentralized control schemes are not suitable for an interconnected power system because there exist strong nonlinear interactions among subsystems.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear decentralized load frequency control of multi‐machine power systems with exponential stability and low L₂ gain against load disturbance

Wang

Liu

2020

This paper proposes a novel nonlinear decentralized control method for a class of multi-machine power systems. The aim is to construct a suitable decentralized feedback control law so as to guarantee that the large-scale interconnected power system is exponentially stable and robust against load fluctuations. To this end, we propose a novel design algorithm based on the backstepping, which involves five steps and actively utilizes the locally measurable part of the tie-line power to improve the performance. The effectiveness of the proposed control scheme is demonstrated through extensive simulation studies.

“…Fuzzy logic control, which is known as a powerful scheme for the control of complicated nonlinear systems, has been extensively applied in industrial processes [1][2][3][4][5][6][7][8]. The method relying on T-S fuzzy models has been widely adopted in steering of complex systems with nonlinearities in recent years [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A new design of output feedback sliding mode controller for T‐S fuzzy‐affine systems

Qiu

Lam

2020

This work focuses on output feedback sliding mode control (SMC) for nonlinear systems via T-S fuzzy affine models. Associated with the sliding surface, a singular system is firstly proposed to describe the dynamical features of the sliding motion. Adopting some convexification techniques and based on piecewise quadratic Lyapunov functions (PQLFs) and a common quadratic Lyapunov function (CQLF), sufficient criteria for the asymptotic stability analysis of the sliding mode dynamical system are attained. Two output feedback SMC synthesis schemes are developed to drive the closed-loop system states to the sliding surface in finite time. A simulation example is presented to show the validity of the proposed methods.