Liang Diao

A DSC approach to synchronized path following of multiple underactuated AUVs with uncertain dynamics and input constrains

This paper is concerned with the synchronized path following problem of multiple underactuated autonomous underwater vehicles (AUVs) in the presence of uncertain dynamics and input constrains. Nonlinear path following controllers are proposed for individual AUV that yield convergence of the position tracking errors to a small neighborhood of the origin. Vehicles coordination is achieved by synchronizing the along-path speed and path variables, as determined by the communications topology adopted. The proposed control design use a combination of neural network (NN), dynamic surface control (DSC) technique and an auxiliary system. The NN based DSC adaptive technique is incorporated to handle the uncertain dynamics, and simplifies the synchronized path following controllers by introducing the first-order filters. Input constrains problem is taken into account with the aid of auxiliary system design. Under the proposed controllers, uniformly ultimately bounded (UUB) of the closed-loop system are guaranteed for all signals. The design procedure is illustrated through the simulation results.

Active disturbance rejection control for stand-alone doubly fed induction generator

In this paper, a controller design method is proposed for stand-alone doubly fed induction generator (DFIG). This method is based on forced stator-voltage-oriented vector control principle and active disturbance rejection control (ADRC) approach. Specifically, the forced stator-voltage-oriented vector control principle is used to simplify the mathematics model of stand-alone DFIG and guarantee constant frequency. ADRC approach is used to obtain the constant amplitude of the stator voltage with the variable load. The proposed strategy has a good transient at the start-up and the load changes condition. Simulation results are given to illustrate the efficacy of the proposed method.

Neural Dynamic Surface Control for Three-Phase PWM Voltage Source Rectifier

In this brief, a neural dynamic surface control algorithm is proposed for three-phase pulse width modulation voltage source rectifier with the parametric variations. Neural networks are employed to approximate the uncertainties, including the parametric variations and the unknown load-resistance. The actual control laws are derived by using the dynamic surface control method. Furthermore, a linear tracking differentiator is introduced to replace the first-order filter to calculate the derivative of the virtual control law. Thus, the peaking phenomenon of the filter is suppressed during the initial phase. The system stability is analyzed by using the Lyapunov theory. Simulation results are provided to validate the efficacy of the proposed controller.

A predictor-based neural modified DSC approach to distributed formation tracking of networked marine surface vehicles

This paper considers the distributed formation tracking of networked marine surface vehicles with model uncertainty and time-varying ocean disturbances induced by wind, waves and ocean currents. The objective is to achieve a collective tracking with a time-varying trajectory, which can only be accessed by a fraction of follower vehicles. Distributed adaptive formation controllers are developed based on a predictor, neural networks, a tracking differentiator, and a dynamic surface control design technique. Instead of the first-order filter commonly used in traditional dynamic surface control design approach, a second-order tracking differentiator is employed to produce a fast and precise estimate of the virtual control signal prescribed by the kinematic control law. The prediction errors, rather than tracking errors, are used to update the neural adaptive laws, which enable fast identifying the vehicle dynamics without incurring high-frequency oscillations in control signals. The stability properties of the closed-loop network are established via Lyapunov analysis. Simulation results are provided to demonstrate the performance improvement of the proposed method.

Cooperative dynamic positioning of multiple offshore vessels via local information interactions

Unlike the traditional dynamic positioning of single marine surface vessel, a local cooperative control scheme is proposed to achieve the dynamic positioning of multiple offshore vessels and rigs subject to the influence of persistent ocean disturbances through a connected communication network. Cooperative dynamic positioning controllers are developed with the aid of a dynamic surface control technique and theory of multi-agent systems. The proposed control laws guarantee that a relative formation among vessels can be achieved even when only a fraction of vessels have access to the reference point. The stability properties of the proposed controllers are established via Lyapunov analysis. Simulation results demonstrate the efficacy of the proposed method.

Adaptive dynamic surface control for three-phase PWM voltage source rectifier

An adaptive controller is designed for three-phase pulse width modulation (PWM) voltage source rectifier with parametric uncertainties based on the dynamic surface control (DSC) technique. The unknown parameters of the system are estimated by applying the adaptive control method. In addition, the problem of “explosion of complexity” in backstepping design procedure is avoided by using the DSC technique. Lyapunov analysis demonstrates that all signals in the closed-loop system are globally uniformly ultimately bounded. The tracking errors of the q axis current and the output voltage converge to a small neighborhood of the origin by appropriately choosing the design parameters. Simulation results validate the efficacy of the proposed controller.

Coordinated pattern tracking of multiple marine surface vehicles with uncertain kinematics and kinetics

This paper considers the coordinated pattern tracking of multiple marine surface vehicles in the presence of uncertain kinematics and kinetics. Distributed pattern tracking controllers depending on the information of neighboring vehicles are derived based on a backstepping technique, neural networks and an identifier. Specifically, the identifier is devised to precisely estimate the time-varying ocean currents at the kinematic level. Neural networks together with adaptive filtering methods are employed to extract the low frequency content of the model uncertainty and ocean disturbances at the kinetic level. The benefit of the proposed design results in adaptive pattern tracking controllers over any undirected connected graphs with guaranteed low frequency control signals, which facilitates practical implementations. The stability properties of the multi-vehicle systems are established via Lyapunov analysis, and the pattern tracking errors converge to an adjustable neighborhood of origin. An example is given to show the performance of the proposed approach.

Coordinated tracking of linear multi-agent systems with a dynamic leader: An iterative learning approach

This paper is concerned with the coordinated tracking of linear multi-agent systems with a dynamic leader. The input of the leader is time-varying and cannot be obtained by any follower agents. Distributed iterative learning controllers are developed based on the relative state information of neighboring agents. Lyapunov-Krasovskii functionals are used to show the stability properties of the closed-loop network. The benefit of the proposed controllers allow for tracking the dynamic leader over any undirected connected graphs. Besides, unknown input of the leader can be identified using distributed iterative learning laws. An extension to dynamic coupling without using global information is further studied. An application to synchronization of autopilots is provided to validate its efficacy.

Sensorless control of a stand-alone Doubly fed induction machine for ship shaft generator systems

This paper presents a position sensorless control strategy of stand-alone doubly fed induction machine (DFIM) used for ship shaft generation systems. Direct voltage control method is used to generate constant frequency and voltage with variable load and main engine speed. The strategy does not need any signal from speed, so the position encoder or estimators are unnecessary. The space vector pulse width modulation (SVPWM) technique is used to reduce the rotor current harmonics and the modification of the reference stator vector angle is applied to achieving the reference stator voltage quickly and successfully. Simulation results are given to illustrate the efficacy of the proposed method.