Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints

By Mou Chen, Shuzhi Sam Ge, Beibei Ren. at - Automatisierungstechnik, 2011

1,028 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/1cf51e8de7f27b49b5eafbefdb2a95f51634ffca

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Shaocheng Tong
2. Yong-ming Li
3. Yanjun Liu
4. Wei He
5. Mou Chen
6. Chun Lung Philip Chen
7. Changyin Sun
8. Hongyi Li

In Control and Systems Engineering

1. Shaocheng Tong
2. Wei He
3. Yong-ming Li
4. Mou Chen
5. Yanjun Liu
6. Hongyi Li
7. Shuzhi Sam Ge
8. Chun Lung Philip Chen

Citations in the corpus

• Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form (2014, background): “Among these, back-stepping has been widely studied because it provides a systematic framework for the design of tracking and regulation strategies, suitable for a large class of state feedback linearizable nonlinear systems [1], [2].”
• Adaptive Trajectory Tracking Control of a Fully Actuated Surface Vessel With Asymmetrically Constrained Input and Output (2018, background): “Therefore, when high damping ratio (ξi ≥ 1) is assigned, the filter states will exponentially converge to the input value and its derivative, respectively, and αi , α̇i are limited by mechanical or operating limitations of virtual control laws and control command [10].”
• Adaptive Fuzzy Control via Observer Design for Uncertain Nonlinear Systems With Unmodeled Dynamics (2013, background): “Several typical results have been designed in adaptive control for nonlinear systems with parameter uncertainties or the uncertainties to be bounded by the pth-order polynomial bounds with unknown constants; see, for example, [1]–[7], [29] and references therein.”
• Adaptive Neural Network Control of a Robotic Manipulator With Time-Varying Output Constraints (2017, background): “In [32], the trajectory tracking problem of multi-input and multi-output (MIMO) nonlinear systems that are uncertain and subjected to input constraints is settled with adaptive NNs.”
• Robust adaptive backstepping control for an uncertain nonlinear system with input constraint based on Lyapunov redesign (2016, methodology): “A first-order filter [22], command filters [23] and robust second order filters [24] are employed to eliminate the complexity computation of time derivative of virtual control inputs to overcome the “explosion of terms” problem.”
• Neural Network Control-Based Adaptive Learning Design for Nonlinear Systems With Full-State Constraints (2016, neutral): “In [3], an adaptive tracking control was proposed for nonlinear multi-input multioutput (MIMO) systems with nonsymmetric input constraints, and the auxiliary system was designed to solve the effect of input constraints.”
• Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation (2016, background): “In [45], adaptive tracking control is presented for a class of uncertain nonlinear systems with input saturation.”
• Teleoperation Control Based on Combination of Wave Variable and Neural Networks (2017, methodology): “The adaptive control method for robots has been studied in a considerable number of works [14]–[16], which could be used in the situations of unknown parameters and time-varying parameters in the robot model [17], [18].”
• Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation (2016, background): “The main contributions of this paper can be summarized as follows: 1) By designing a fuzzy state observer to estimate the unmeasured states, the proposed adaptive control approach can cancel the restrictive condition in [16], [17], [19], [22], [23], [25], [26] that all the states of the controlled n”
• Robust Adaptive Fuzzy Tracking Control for Pure-Feedback Stochastic Nonlinear Systems With Input Constraints (2013, methodology): “The main differences between our result and the ones in [29], [39], and [47] are as follows: 1) From the controlled systems, the results are obtained in [39] and [47] for deterministic systems and in [29] for the strict-feedback stochastic system without input saturation, and in this paper, we consi”
• Fault tolerant finite-time leader-follower formation control for autonomous surface vessels with LOS range and angle constraints (2016, methodology): “More discussion regarding the auxiliary system in similar designs can be found in Chen et al. (2010, 2011) and Jin (2016).”