Composite Adaptive Fuzzy Output Feedback Control Design for Uncertain Nonlinear Strict-Feedback Systems With Input Saturation

Abstract

In this paper, a composite adaptive fuzzy output-feedback control approach is proposed for a class of single-input and single-output strict-feedback nonlinear systems with unmeasured states and input saturation. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy state observer is designed to estimate the unmeasured states. By utilizing the designed fuzzy state observer, a serial-parallel estimation model is established. Based on adaptive backstepping dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial-parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws are developed. It is proved that all the signals of the closed-loop system are bounded and the system output can follow the given bounded reference signal. A numerical example and simulation comparisons with previous control methods are provided to show the effectiveness of the proposed approach.

Adaptive Neural Output Feedback Control for Uncertain Robot Manipulators with Input Saturation

“…The compounded disturbance is estimated using the disturbance observer which is proposed as (20). Using the output of the state observer, the disturbance observer, and the RBFNN, the adaptive neural output feedback control of the robot manipulator is designed as (40) and the parameter updated laws are chosen as (48).…”

“…The unknown compounded disturbance is estimated using the disturbance observer (20). Using the outputs of the state observer, the disturbance observer, and the RBFNN, the adaptive neural output feedback control for the robot manipulator is designed as (40), with the parameter updated laws (48). Then, all closed-loop system signals are semiglobally uniformly bounded under the proposed disturbance observer based adaptive neural output feedback control scheme.…”

“…When parameter change, disturbances, or state errors become large, the required input torques will quickly reach saturation due to the needed massive control effort to maintain tracking control performance for robotic manipulators [44][45][46][47][48][49][50][51][52]. Under this case, the unchanged control output will destroy the stability of the closed-loop control systems.…”

Command filter based globally stable adaptive neural control for cooperative path following of multiple underactuated autonomous underwater vehicles with partial knowledge of the reference speed

“…Before introducing our control design method, let us first recall the approximation property of the NNs [11][12][13][14][36][37][38][39][40][41][42][43][44][45] . The NNs take the form of W T σ ( ξ ) where W ∈ R ×m is called weight matrix, with being the number of NN nodes; and σ (ξ ) ∈ R is a vector valued function defined in R , with ξ ∈ R q being the NN input vector.…”

H∞ Tracking Control of Fuzzy Dynamic Output for Nonlinear Networked System with Packet Dropouts

“…In some fields, the tracking control of output is employed far and wide, such as motors [8,9], robots [10], and flights [11]. Based on the tracking control of output, many preliminary studies have been produced [12][13][14][15]. Papers [6,[16][17][18] proposed some questions about stability, and some scholars proposed some thinking about ∞ control [19] as well as the problem of designing about the filter in the literature [20].…”