Weiyao Lan

Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics

In this brief, we consider the formation control problem of underactuated autonomous surface vehicles (ASVs) moving in a leader-follower formation, in the presence of uncertainties and ocean disturbances. A robust adaptive formation controller is developed by employing neural network and dynamic surface control technique. The stability of the design is proven via Lyapunov analysis where semiglobal uniform ultimate boundedness of the closed-loop signals is guaranteed. The advantages of the proposed formation controller are that: first, the proposed method only uses the measurements of line-of-sight range and angle by local sensors, no other information about the leader is required for control implementation; second, the developed neural formation controller is able to capture the vehicle dynamics without exact information of coriolis and centripetal force, hydrodynamic damping and disturbances from the environment. Comparative analysis with a model-based approach is given to demonstrate the effectiveness of the proposed method.

A Hard-Disk-Drive Servo System Design Using Composite Nonlinear-Feedback Control With Optimal Nonlinear Gain Tuning Methods

This paper investigates the design of composite nonlinear-feedback (CNF) control law for a hard-disk-drive (HDD) servo system. First, a scaled nonlinear function is introduced for the CNF control law, in which a parameter is scaled by the error between the amplitude of the target reference and the initial value of the system controlled output. The closed-loop system under the scaled function has robust transient performance to the variation of the amplitude of the target reference. Then, the parameters of the selected nonlinear function are tuned by optimal tuning methods. More specifically, the parameter-tuning problem is formulated as an optimization problem, which can be solved efficiently via numerical methods. The simulation and experimental results show that the control law designed using the new approach yields excellent performance for both track seeking and track following in the HDD servo system.

Semiglobal stabilization and output regulation of singular linear systems with input saturation

The semi-global stabilization problem and output regulation problem of singular linear systems subject to input saturation are addressed. A reduced-order normal system is obtained by a standard coordinate transformation. It is further shown that the controller that solves the stabilization (output regulation) problem of the reduced-order normal systems also solves the stabilization (output regulation) problem of the original singular systems.

On improvement of transient performance in tracking control for a class of nonlinear systems with input saturation

This paper studies the technique of the composite nonlinear feedback (CNF) control for a class of cascade nonlinear systems with input saturation. The objective of this paper is to improve the transient performance of the closed-loop system by designing a CNF control law such that the output of the system tracks a step input rapidly with small overshoot and at the same time maintains the stability of the whole cascade system. The CNF control law consists of a linear feedback control law and a nonlinear feedback control law. The linear feedback law is designed to yield a closed-loop system with a small damping ratio for a quick response, while the nonlinear feedback law is used to increase the damping ratio of the closed-loop system when the system output approaches the target reference to reduce the overshoot. The result has been successfully demonstrated by numerical and application examples including a flight control system for a fighter aircraft.

Composite nonlinear feedback control for linear singular systems with input saturation

Abstract This paper investigates the composite nonlinear feedback (CNF) control technique for linear singular systems with input saturation. First, a linear feedback control law is designed for the step tracking control problem of linear singular systems subject to input saturation. Then, based on this linear feedback gain, a CNF control law is constructed to improve the transient performance of the closed-loop system. By introducing a generalized Lyapunov equation, this paper develops a design procedure for constructing the CNF control law for linear singular systems with input saturation. After decomposing the closed-loop system into fast subsystem and slow subsystem, it can be shown that the nonlinear part of the CNF control law only relies on slow subsystem. The improvement of transient performance by the proposed design method is demonstrated by an illustrative example.

On Improving Transient Performance in Tracking Control for a Class of Nonlinear Discrete-Time Systems With Input Saturation

Quick response and small overshoot are two desired transient performances of target tracking control. While most of the design schemes compromise between these two performances, we try to achieve both simultaneously for the tracking control of a class of nonlinear discrete-time systems with input saturation by using a composite nonlinear feedback (CNF) control technique. The closed-loop system with improved transient performance preserves the stability of the nonlinear part of the partially linear composite system.

On selection of nonlinear gain in composite nonlinear feedback control for a class of linear systems

This paper addresses the tuning of the nonlinear function in the composite nonlinear feedback (CNF) control law for single-input single-output linear systems. A new nonlinear function is proposed for the CNF control law. The parameters of the new function are not sensitive to variation of amplitude of the reference input. The parameters can be tuned automatically by solving a minimization problem. Two performance criteria, the integral of absolute-value of error (IAE) and the integral of time multiplied absolute-value of error (ITAE), are investigated. Simulation results show that both performance indexes can be used to tune the parameter, but ITAE criterion results in a smaller overshoot than IAE does. Further more, a feedforward neural network is trained to tune the parameter for double integrator systems. The well trained neural network is applied to design a CNF control law for the HDD servo system.

Distributed Average Tracking for Reference Signals With Bounded Accelerations

In this technical note, the distributed average tracking (DAT) problem for reference signals with bounded accelerations is considered. A sliding-mode surface is designed such that trajectories on the surface will achieve DAT. A discontinuous control algorithm is then proposed to guarantee that the surface can be reached in finite time. It is shown that if the switching network topology is connected at all time, then DAT can be solved by properly choosing a gain parameter of the algorithm.

Neural network-based robust adaptive control of nonlinear systems with unmodeled dynamics

A neural network-based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input-output models with an unknown nonlinear function and unmodeled dynamics. By on-line approximating the unknown nonlinear functions and unmodeled dynamics by radial basis function (RBF) networks, the proposed approach does not require the unknown parameters to satisfy the linear dependence condition. It is proved that with the proposed control law, the closed-loop system is stable and the tracking error converges to zero in the presence of unmodeled dynamics and unknown nonlinearity. A simulation example is presented to demonstrate the method.

Robust adaptive neural control of uncertain pure-feedback nonlinear systems

A robust adaptive neural control design approach is presented for uncertain pure-feedback nonlinear systems. In the control design process, only one neural network is used to approximate the lumped unknown part of the systems, and the problem of complexity growing existing in conventional methods can be eliminated completely. The result of stability analysis shows that the proposed scheme can guarantee the uniform ultimate boundedness of the closed-loop system signals, and the control performance can be guaranteed by an appropriate choice of the control parameters. A simulation example is given to demonstrate the effectiveness of the proposed approach.