Adaptive fuzzy visual tracking control for manipulator with quantized saturation input

IET Control Theory & Applications

et al. 2020

This study proposes an adaptive quantised fuzzy control strategy for a class of non-linear systems with time-varying delay, state constraints, and input unmodelled dynamics. Design difficulties focus on the fact that the input-quantised actuator possesses both unknown control gain and non-linear input unmodelled dynamics, and all the states are required to satisfy state constraints. To remove these obstacles, integral barrier Lyapunov functions combined with Nussbaum functions are designed to deal with the unknown control gains and state constraints, and a quantised controller combined with the normalised signal is developed to tackle the quantised input and input unmodelled dynamics. To avoid the chattering and reduce the quantisation error in a wide scope of the control volume, a novel logarithmic uniform hysteresis quantiser is employed, which has both advantages of the existing uniform quantiser and hysteresis quantiser. Two simulation examples of practical control systems are conducted to demonstrate the effectiveness of the proposed control protocol.

Section: Introductionmentioning

confidence: 99%

“…Quantisation can save communication bandwidth, but also bring stronger non-linearity to the system. Therefore, some adaptive quantised control results have been presented in [5][6][7][8][9][10][11][12][13][14]. An adaptive backstepping stabilisation scheme was proposed for a non-linear uncertain system with a quantised input signal in [5].…”

Section: Introductionmentioning

confidence: 99%

Adaptive quantised control of uncertain non‐linear systems with state constraints and time‐varying delays

Xia

Kang

IET Control Theory & Applications

et al. 2020

“…Depending on a subtle controller design, Yu and Yan removed several strict assumptions of the system in the work of Zhou et al An adaptive tracking scheme was studied for uncertain nonlinear systems with quantized input and unknown parameters in the work of Choi and Yoo . Adaptive fuzzy visual control was developed for manipulator with quantized saturation input in the work of Wang et al On the other hand, the logarithmic quantizer presented in the work of Elia and Mitter was proved to be the most efficient for Lyapunov stabilization. To prevent the chattering appearing while the states or the control law varied around the boundary point of quantization, the hysteresis logarithmic quantizer was designed in the works of De Persis and Mazenc( and Ceragioli et al This quantizer was widely applied to adaptive quantized control in related works.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive quantized DSC of uncertain pure‐feedback nonlinear systems with time‐varying output and state constraints

Xia

Intl J Robust & Nonlinear

2018

In this paper, the problem of neural adaptive dynamic surface quantized control is studied the first time for a class of pure-feedback nonlinear systems in the presence of state and output constraint and unmodeled dynamics. The considered system is under the control of a hysteretic quantized input signal. Two types of one-to-one nonlinear mapping are adopted to transform the pure-feedback system with different output and state constraints into an equivalent unconstrained pure-feedback system. By designing a novel control law based on modified dynamic surface control technique, many assumptions of the quantized system in early literary works are removed. The unmodeled dynamics is estimated by a dynamic signal and approximated based on neural networks. The stability analysis indicates that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the output and all the states remain in the prescribed time-varying or constant constraints. Two numerical examples with a coarse quantizer show that the proposed approach is effective for the considered system. KEYWORDSadaptive quantized control, output and state constraints, pure-feedback systems, robust adaptive DSC, unmodeled dynamics Int J Robust Nonlinear Control. 2018;28:3357-3375. wileyonlinelibrary.com/journal/rnc

“…Along the line of quantized control input, some novel results are given in literature. [22][23][24][25][26][27][28] By utilizing uniform quantizer, 22 the control signals are divided into equivalent and average quantization blocks, yet, this kind of quantizer is generally not applicable to the asymptotically tracking control since only fixed quantization level is available even if exact quantization precision is required. To overcome this issue, logarithmic quantizers are adopted in the works by Fu and Xie 23 and Xing et al, 24 and the adaptive control schemes are based upon the sector-bounded property of quantization errors to design appropriate control laws.…”

Section: Introductionmentioning

confidence: 99%

“…To overcome this issue, logarithmic quantizers are adopted in the works by Fu and Xie 23 and Xing et al, 24 and the adaptive control schemes are based upon the sector-bounded property of quantization errors to design appropriate control laws. In previous literature, [25][26][27][28] hysteretic quantizer, which can be regarded as a combination of two logarithmic quantizers with identical gain but opposite direction, is used to avoid chattering phenomenon. However, the above results assume that the structural property and exact parametric knowledge of the adopted quantizer are known in the controller design, which seems unpractical since the model parameters are user-defined and adjusted to obtain optimal control performances.…”

Section: Introductionmentioning

confidence: 99%

Adaptive bilateral control of teleoperators with actuator uncertainty and quantized input

Wang

Liu

Advances in Mechanical Engineering

2017

Self Cite

This article addresses the control and stabilization problem of bilateral teleoperator system with input quantized by the so-called hysteresis-type quantizer, where the joint actuator model, robot dynamics, and kinematics are uncertain. In order to overcome the control issue that only discrete and finite control values can be applied to the robot dynamics, a decomposition-based technique is adopted to cope with the quantized control signals. By incorporating the Nussbaumgain function to the proposed controller, an adaptive telecontrol scheme together with the parameter updating laws is developed to achieve position and velocity tracking of teleoperator system in the presence time delays without a priori knowledge of actuator and quantizer model parameters, upon which, the robot dynamics and kinematics uncertainties are also effectively accommodated. It is proven by the Lyapunov method that the closed-loop dynamics are bounded, and the position as well as velocity tracking errors converges to zero. Simulation results verify the proposed adaptive telecontrol scheme.