A novel intelligent control scheme is presented for accurate position tracking of electrohydraulic servo actuators. The proposed control law is designed by means of a non-linear control approach and includesan adaptive neural network to provide the basic intelligent features. Online learning, instead of off-line supervised training, is proposed to update the weight vector of the neural network. Moreover, the adoption of a composite error signal as the only input to the neural network allows a significant reduction in the computational complexity of the algorithm. Rigorous proofs for the boundedness and convergence properties of the closed-loop signals are provided. Experimental results obtained with an electrohydraulic system demonstrate the...
[[abstract]]A novel scheme investigating a radial-basis-function neural network (RBFNN) with variabl...
This paper proposes an advanced position-tracking control approach, referred to as an integrated int...
A novel intelligent neural network control scheme which integrates the merits of fuzzy inference, ne...
This paper proposes a neural network based controller for controlling the position of an electrohydr...
Electrohydraulic servomechanisms are well known for their fast dynamic response, high power to iner...
A new model reference adaptive control design method using neural networks that improves both transi...
This work describes the development of a nonlinear control strategy for an electro-hydraulic actuate...
To satisfy the lightweight requirements of large pipe weapons, a novel electrohydraulic servo (EHS) ...
[[abstract]]An adaptive neural-network tracking control with a guaranteed H infinity performance is ...
Abstract. An adaptive backstepping neural network position controller design is presented for the el...
A complete study of the development of a nonlinear backstepping controller for an electrohydraulic s...
This chapter utilizes the direct neural control (DNC) based on back propagation neural networks (BPN...
Realization of biologically motivated algorithms in industrial applications is becoming a new resear...
[[abstract]]An adaptive neural-network tracking control with a guaranteed H ∞ performance is propose...
Abstract—An adaptive neural-network tracking control with a guaranteedH1 performance is proposed for...
[[abstract]]A novel scheme investigating a radial-basis-function neural network (RBFNN) with variabl...
This paper proposes an advanced position-tracking control approach, referred to as an integrated int...
A novel intelligent neural network control scheme which integrates the merits of fuzzy inference, ne...
This paper proposes a neural network based controller for controlling the position of an electrohydr...
Electrohydraulic servomechanisms are well known for their fast dynamic response, high power to iner...
A new model reference adaptive control design method using neural networks that improves both transi...
This work describes the development of a nonlinear control strategy for an electro-hydraulic actuate...
To satisfy the lightweight requirements of large pipe weapons, a novel electrohydraulic servo (EHS) ...
[[abstract]]An adaptive neural-network tracking control with a guaranteed H infinity performance is ...
Abstract. An adaptive backstepping neural network position controller design is presented for the el...
A complete study of the development of a nonlinear backstepping controller for an electrohydraulic s...
This chapter utilizes the direct neural control (DNC) based on back propagation neural networks (BPN...
Realization of biologically motivated algorithms in industrial applications is becoming a new resear...
[[abstract]]An adaptive neural-network tracking control with a guaranteed H ∞ performance is propose...
Abstract—An adaptive neural-network tracking control with a guaranteedH1 performance is proposed for...
[[abstract]]A novel scheme investigating a radial-basis-function neural network (RBFNN) with variabl...
This paper proposes an advanced position-tracking control approach, referred to as an integrated int...
A novel intelligent neural network control scheme which integrates the merits of fuzzy inference, ne...