Quantization‐based switched second‐order sliding mode control for uncertain systems

Abstract

A novel quantization-based switched second-order sliding mode control design is considered for nonlinear uncertain systems. A new quantization strategy associated with state-space partition is utilized to accommodate the control amplitude to different uncertainty levels then the conservatism of the control gain is thus attenuated. Investigating each quantized region, it is obtained that all regions are globally invariant sets which offers a monotonously consecutive decrease of the quantized control amplitude when sliding variable converging to the origin through considered uncertainty levels. To deal with different control objectives, the closed-loop system performance can be enhanced via adapting the quantization parameters. The finite-time stability analysis and the effect assessment of quantization parameter on the total convergence time are provided. Simulation shows the efficacy and superiority compared with referenced methods.

Fixed‐time sliding mode trajectory tracking control for marine surface vessels under mismatched conditions and input saturation

“…As a promising control method, it is well known that sliding mode control (SMC) has superior and favorable capacities to reject the matched bounded perturbations including parametric variations and exogenous disturbances. 10 Because of the excellent characteristics of SMC, it has been employed to the trajectory tracking control of an MSV. In Reference 11, SMC is employed to tackle tracking control problem and ensure robustness for an underactuated MSV.…”

“…In the published literature, for the purpose of improving the control performance, many superior control methods have been applied to control scheme designs, such as backstepping control, 5 model predictive control, 6 adaptive fuzzy control, 7 adaptive neural network control, 8 proportional‐integral funnel control, 9 and so forth. As a promising control method, it is well known that sliding mode control (SMC) has superior and favorable capacities to reject the matched bounded perturbations including parametric variations and exogenous disturbances 10 . Because of the excellent characteristics of SMC, it has been employed to the trajectory tracking control of an MSV.…”

Right Coprime Factorization-Based Simultaneous Control of Input Hysteresis and Output Disturbance and Its Application to Soft Robotic Finger

“…For example, research on soft actuators and aluminum plates with Peltier devices have been carried out in [5][6][7], which implied the robustness of RCF systems even with uncertainty. What is more, an intelligent robust operator-based sliding mode control method was proposed in [8], which made RCF theory combine with sliding mode control so as to obtain better tracking performance in nonlinear control system. Therefore, RCF theory is introduced in this paper to achieve robust control combined with the decomposition of hysteresis mentioned above.…”

Neuroadptive quantization tracking control with accelerate convergence rate for self‐restructuring systems

“…On the other hand, signal quantization, which can be viewed as a map from continuous signals to discrete finite sets, is not only required in implementation of control algorithms in digital devices, but also significantly reduce communication pressure and improve communication efficiency, 8 thus has received a great deal of attention from researchers in networked control systems 9 . In recent years, quantification has gradually developed from linear systems 10,11 to nonlinear systems 12‐17 . The quantization nature brings additional technical challenge to control design and stability analysis.…”

“…9 In recent years, quantification has gradually developed from linear systems 10,11 to nonlinear systems. [12][13][14][15][16][17] The quantization nature brings additional technical challenge to control design and stability analysis. In Reference 13, a backstepping-based quantization adaptive control scheme is developed for a class of strict feedback nonlinear systems.…”