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Collision Avoidance for Vehicle Platoon with Input Deadzone
Published in Xiang-Gui Guo, Jian-Liang Wang, Fang Liao, Rodney Teo, Multi-Agent Systems, 2019
Xiang-Gui Guo, Jian-Liang Wang, Fang Liao, Rodney Teo
This chapter investigates the adaptive platoon controlplatoon control for nonlinear vehicular systems with asymmetric nonlinear input deadzone and neighboring vehicular spacing constraints. Vehicular platoon controlplatoon control encounters great challenges from unmodeled dynamic uncertainties, unknown external disturbancesexternal disturbances, unknown asymmetric nonlinear input deadzone and neighboring vehicular spacing constraints. In order to avoid collisions between consecutive vehicles as well as the connectivity breaks owing to limited sensing capabilities, a symmetric barrier Lyapunov function is employed. Then, a neural-network-based terminal sliding mode controlsliding mode control (TSMC) scheme with minimal learning parameters is developed to maintain neighboring-vehicles keep connectivity and simultaneously avoid collisions. The uniform ultimate boundedness of all signals in the whole vehicular platoon controlplatoon control system is proven via Lyapunov analysis.
ESO-Based Terminal Sliding Mode Control Under Periodic Event-Triggered Protocol
Published in Jun Song, Zidong Wang, Yugang Niu, Protocols-Based Sliding Mode Control, 2023
Jun Song, Zidong Wang, Yugang Niu
Inspired by the aforementioned discussions, in this chapter, we endeavour to proposed a novel periodic event-triggered terminal sliding mode control (TSMC) approach and implement it to a speed regulation problem in PMSM. In periodic event-triggered method, the continuous state measurement is no longer required due to the periodic evaluation of the triggering rule. This just means that the triggering time is always an integral multiple of the sampling period which avoids the Zeno phenomenon. Besides, an extended-state-observer (ESO) is introduced to estimate the unknown perturbations in PMSM mainly arising from the external disturbance and the parameter uncertainties. The main contributions of this chapter can be concluded as follows: 1) Based on a nonsingular terminal sliding function, a novel ESO-based periodic event-triggered TSMC is designed for the networked PMSM speed regulation system, in which the explicit upper-bound of the ESO estimation error is given; 2) The actual bound of the triggering error is analyzed with proposing a proper selection criterion of the periodic sampling period; 3) A design condition for the controller gain is established for ensuring the reachability to a sliding domain and the ultimate boundedness of the closed-loop PMSM speed regulation system; 4) In order to reduce the chattering and the communication burden simultaneously, a binary-based genetic algorithm (GA) is formulated to get the optimized ESO with the ideal estimation error; and 5) The effectiveness of the proposed novel periodic event-triggered TSMC scheme with GA-optimized ESO is demonstrated in both of the simulation and experiment results.
Safety Control System Design of HGV Based on Adaptive TSMC
Published in Xiang Yu, Lei Guo, Youmin Zhang, Jin Jiang, Autonomous Safety Control of Flight Vehicles, 2021
Xiang Yu, Lei Guo, Youmin Zhang, Jin Jiang
This chapter presents a safety control strategy for a hypersonic gliding vehicle (HGV) subject to actuator malfunctions and model uncertainties. The control-oriented model of the HGV is established according to the HGV kinematic and aerodynamic models. A composite-loop design for HGV safety control under actuator faults is subsequently developed, where newly developed multivariable integral terminal sliding-mode control (TSMC) and adaptive techniques are integrated. The simulations show that the HGV can handle the time-invariant, the time-varying actuator faults and model uncertainties well with the proposed safety control design techniques.
Design of rapid exponential integral nonlinear tracking differentiator
Published in International Journal of Control, 2022
Zhenzhen Chen, Xiju Zong, Wenjie Tang, Danhui Huang
The terminal attractor function used in this paper is inspired by the sliding mode control theory. The terminal attractor function in sliding mode control theory is , where both m>0 and n>0 are odd. In this paper, the value of the terminal attractor function is similar to the terminal sliding mode. Terminal sliding mode can weaken chattering, so use terminal attractor function to enhance noise suppression. The linear function is used in (4) as part of the tracking differentiator, which is different from Shao and Wang (2014); Tan et al. (2019) and is innovative. The linearity of the function near the equilibrium can increase the rate of convergence near the equilibrium point.
ESO based sliding mode control for the welding robot with backstepping
Published in International Journal of Control, 2021
Pengcheng Wang, Dengfeng Zhang, Baochun Lu
FTSMC: The fast terminal sliding mode control is a kind of sliding mode control strategy which is compared with the ordinary sliding mode control. The fast terminal sliding mode control is to introduce the nonlinear function in the design of the sliding mode surface, and to construct the terminal sliding mode surface. The tracking error on the sliding surface can converge to zero within the specified finite time . In this paper, the saturation function is substituted for the switching function, the boundary layer thickness is δ = 0.2. The nonlinear sliding surface is designed as and , the control law parameters are taken , , . The boundary layer thickness and the sliding mode surface parameters can be found during the simulation, which has an influence on the whole control process.
Match and mismatched second-order sliding mode finite-time control with simple parameter conditions and its applications
Published in Journal of Control and Decision, 2021
Among these finite-time control methods, SMC is widely used (Man et al., 1994; Mobayen, 2015; Venkataraman & Gulati, 1991). The design process of SMC is divided into two parts (Mobayen, 2015), which are sliding mode surface design and control law design. In the traditional linear sliding mode control, the system state reaches the sliding surface, and it approaches the origin according to the exponential law. Although the convergence speed can be adjusted by parameters, its steady-state error cannot converge to zero in a finite time, which limits its application. Venkataraman and Gulati (1991) and Man et al. (1994) proposes terminal sliding mode, which mainly uses nonlinear sliding mode instead of traditional linear sliding mode, which makes the system state converge to equilibrium point for finite time.