Unknown Time-varying External Disturbances Research Articles

PTESO based robust stabilization control and its application to 3-DOF ship-borne parallel platform

In this paper, a prescribed-time extended state observer (PTESO) is constructed for a three degree-of-freedom (3-DOF) parallel ship-borne platform to estimate the platform’s total disturbances, including dynamic uncertainties, unknown time-varying external disturbances and coupling between the platform motion state variables. The constructed PTESO offers the advantages of converging within a prescribed time, suppressing initial peaking phenomenon and easy implementation. Furthermore, a PTESO based PD-like robust stabilization control law is designed, which maintains the support surface of the platform at a given horizontal position and orientation in the inertial space. Theoretical analyses show that the resulting closed-loop stabilization control system is stable. Simulation results with comparisons are presented to verify the effectiveness of our proposed robust stabilization control strategy.

Distributed finite-time velocity-free robust formation control of multiple underactuated AUVs under switching directed topologies

This paper proposes a distributed finite-time velocity-free robust formation control scheme for multiple underactuated autonomous underwater vehicles (AUVs) under switching directed topologies in the presence of uncertain dynamics and unknown time-varying external disturbances. Here, a novel finite-time velocity observer is created for each AUV to estimate its neighbors’ velocities within a finite time so that only its neighbors’ positions need to be transmitted, which reduces the communication burden between AUVs. Then, a super-twisting extended state observer is constructed for each AUV to estimate its total disturbances lumped by the uncertain dynamics and the unknown time-varying external disturbances, whose estimation errors can converge to zero within a finite time. Further, a distributed finite-time velocity-free robust formation control law is proposed incorporating the above into the nonsingular terminal sliding mode technique. Theoretical analysis and simulation results indicate that the proposed formation control law can make the multiple AUVs achieve the desired formation pattern while guaranteeing the formation errors converge to zero within a finite time.

Fast fixed-time vertical plane motion control of autonomous underwater gliders in shallow water

In this paper, a fast fixed-time vertical plane motion controller is proposed for autonomous underwater gliders (AUGs) gliding in shallow water. The influence of speed-sensorless conditions, model uncertainties, unknown time-varying external disturbances, input saturations, and state delay are taken into account. To improve control performance, a fast fixed-time stable system is first presented. Based on the system, an adaptive extended state observer (ESO) is developed for estimating speed, model uncertainties, and external disturbances. A fast fixed-time controller is designed for improving the gliding efficiency and reducing the risk of hitting the ocean floor. Moreover, an input saturation auxiliary system and an advance compensation method are presented to cope with input saturations and state delay. According to Lyapunov theory, it is proved that the AUG states can converge into a small neighborhood within a fixed time. Finally, simulation results demonstrate the rapidity and effectiveness of the designed control method.

Spectral Entropy Analysis and Synchronization of a Multi-Stable Fractional-Order Chaotic System using a Novel Neural Network-Based Chattering-Free Sliding Mode Technique

Abstract An immense body of research has focused on chaotic systems, mainly because of their interesting applications in a wide variety of fields. A comprehensive understanding and synchronization of chaotic systems play pivotal roles in practical applications. To this end, the present study investigates a multi-stable fractional-order chaotic system. Firstly, some dynamical features of the system are described, and the chaotic behaviour of the system is verified. Then, both spectral entropy and spectral Min-Entropy are computed, and the phenomenon of multi-stability is shown. Besides, the combination of a new chattering-free robust sliding mode controller with a neural network observer is proposed for the synchronization of the fractional-order system. With the neural network estimator, unknown functions of the system are obtained, and the effects of disturbances are completely taken into account. Also, based on the Lyapunov stability theorem, the asymptotical stability of the closed-loop system is confirmed. Lastly, the proposed control technique is applied to the fractional-order system. Numerical results demonstrate the chattering-free and effective performance of the proposed control method for uncertain systems in the presence of unknown time-varying external disturbances.

Modeling and Nonlinear Robust Tracking Control of a Three-Rotor UAV Based on RISE Method

In this paper, the flight principle and accurate dynamics of three-rotor unmanned aerial vehicle (UAV) are detailedly analyzed and a nonlinear robust tracking control strategy is proposed considering unknown time-varying external disturbances. Aiming at the tracking control of the typical underactuated system, the dynamic model of the three-rotor UAV is divided into outer-loop position subsystem and inner-loop attitude subsystem. The feedback linearization algorithm is employed to design the outer-loop controller for the trajectory tracking of the UAV. For the inner-loop control of the UAV, the robust integral of the signum of the error (RISE) method is utilized to formulate the robust attitude controller to deal with the external disturbances. The stability of the closed loop system and the asymptotical tracking of the desired trajectory are proved via Lyapunov based stability analysis. Real-time experiments are implemented to validate the performance of the proposed control strategy.

Adaptive robust sliding mode control of autonomous underwater glider with input constraints for persistent virtual mooring

Bottom-resting capability will enable an autonomous underwater glider (AUG) to perform long-duration virtual mooring. However, the tracking control of AUG soft landing on the seabed faces a number of challenges. It is crucial that the controller is able to incorporate many important factors, e.g., model uncertainty, environmental disturbances and limited dynamic range of actuators. This study first formulates the soft landing tracking control problem of AUG for persistent virtual mooring. An adaptive robust control scheme based on sliding mode control with a nonlinear disturbance observer is proposed that can effectively solve the challenges aroused by parametric uncertainty and unknown time-varying external disturbances. Moreover, the effect of input constraints of the AUG system is analyzed for the first time and is damped through a dynamic auxiliary compensator. Finally, simulation results demonstrate the superiority and inherent robustness of the proposed control scheme, in comparison with other techniques.

Adaptive Neural Network Stabilization Control of Underactuated Unmanned Surface Vessels With State Constraints

This paper studies the stabilization problem for the non-diagonal inertia and damping matrices underactuated unmanned surface vessels (USVs) in the presence of unknown time varying environment disturbances and state constraints. In this framework, we first convert the mathematical model into a form of two subsystems, which is easier amenable for stabilization, by applying several transformations. It is proved that the investigated problem can be reduced to one of the second subsystem. A novel time-varying state feedback control scheme based on backstepping method and prescribed Lyapunov function is proposed to ensure state constraints and guarantee the global stability of the reduced control system, as well as sufficient conditions to ensure controller feasibility are given. With adaptive neural networks (NNs), the controller can be easily extended to compensate uncertainty induced by unknown time-varying external disturbances (e.g., wind, waves, and currents). It is proved that all the states and stabilization functions in the overall closed-loop are globally uniformly bounded. Finally, simulation results demonstrate the effectiveness of the proposed control scheme.

Disturbance-observer-based sampled-data adaptive output feedback control for a class of uncertain nonlinear systems

ABSTRACTIn this paper, a sampled-data adaptive output feedback controller is proposed for a class of uncertain nonlinear systems with unmeasured states, unknown dynamics and unknown time-varying external disturbances. To approximate uncertain nonlinear functions, radial basis function neural networks (RBFNNs) are employed. The state observer and the disturbance observer (DO) are constructed to estimate the unmeasured state and the external disturbance, respectively. Then, the sampled-data adaptive output feedback controller and adaptive laws are designed by using the backstepping design technique. The allowable sampling period T is derived to guarantee that all states of the resulting closed-loop system are semi-globally uniformly ultimately bounded. Finally, two simulation examples are presented to illustrate the effectiveness of the proposed approach.

Asymptotic Regulation of Dynamically Positioned Vessels with Unknown Dynamics and External Disturbances

A robust adaptive nonlinear asymptotic regulating control law is designed for dynamically positioned vessels exposed to unknown time-varying external disturbances incorporating Fuzzy Logic Systems (FLSs), projection operators, and the “robustifying” term into the vectorial backstepping technique. The FLSs approximate the vessel unknown dynamics and the update laws based on the online projection operators update the fuzzy weight vectors. The robustifying term handles the external disturbances and the fuzzy approximation errors. The designed Dynamic Positioning (DP) control law achieves asymptotic regulation of the vessel's position and heading and makes the other signals in the DP closed-loop control system of vessels be uniformly ultimately bounded. Simulations based on the Marine System Simulator toolbox validate the designed DP control law.

Robust Adaptive Path Following Control of an Unmanned Surface Vessel Subject to Input Saturation and Uncertainties

This paper investigates the path following control problem of an unmanned surface vessel (USV) subject to input saturation and uncertainties including model parameters uncertainties and unknown time-varying external disturbances. A nonlinear robust adaptive control scheme is proposed to address the issue, more specifically, steering a USV to follow the desired path at a certain velocity assignment despite the involved disturbances, by utilizing the finite-time currents observer based line-of-sight (LOS) guidance and radial basis function neural networks (RBFNN). Backstepping and Lyapunov’s direct method are the main design frameworks. Based on the finite-time currents observer and adaptive control technique, an improved LOS guidance law is proposed to obtain the desired approaching angle to the desired path, making compensations for the effects of unknown time-varying ocean currents. Then, a kinetic controller with the capability of uncertainties estimation and disturbances rejection is proposed based on the RBFNNs, where the adaptive laws including leakage terms estimate the approximation error and the unknown time-varying disturbances. Subsequently, sophisticated auxiliary control systems are employed to handle input saturation constraints of actuators. All error signals of the closed-loop system are proved to be locally uniformly ultimately bounded (UUB). Numerical simulations demonstrated the effectiveness and robustness of the proposed path following control method.

Constrained Control Allocation for Overactuated Aircraft Using a Neurodynamic Model

In this paper, a constrained control allocation scheme is designed based on the neurodynamic model for an overactuated aircraft with system uncertainties and unknown time-varying external disturbances. To generate the control command signals, an adaptive neural attitude controller is developed, taking into consideration the nonsymmetric input saturation constraint. This control scheme can guarantee semi-global uniform ultimate boundedness for all signals in the closed-loop system. The control command signals are sent to the actuators of the overactuated aircraft via the constrained control allocation scheme. Based on the developed adaptive neural attitude control scheme, the control allocation is designed with the position and rate constraints of actuators taken into account. We pose this constrained control allocation as a convex nonlinear programming problem and use a recurrent neural network as its solver. Simulation study on a near space vehicle is conducted to illustrate the effectiveness of the developed adaptive neural attitude control scheme and the constrained control allocation scheme.

38 POSTER Phase I and pharmacological study of KRN951, a potent VEGFR tyrosine kinase inhibitor given in a 4 week on, 2 week off schedule in patients with advanced solid tumors

An immense body of research has focused on chaotic systems, mainly because of their interesting applications in a wide variety of fields. A comprehensive understanding and synchronization of chaotic systems play pivotal roles in practical applications. To this end, the present study investigates a multi-stable fractional-order chaotic system. Firstly, some dynamical features of the system are described, and the chaotic behaviour of the system is verified. Then, both spectral entropy and spectral Min-Entropy are computed, and the phenomenon of multi-stability is shown. Besides, the combination of a new chattering-free robust sliding mode controller with a neural network observer is proposed for the synchronization of the fractional-order system. With the neural network estimator, unknown functions of the system are obtained, and the effects of disturbances are completely taken into account. Also, based on the Lyapunov stability theorem, the asymptotical stability of the closed-loop system is confirmed. Lastly, the proposed control technique is applied to the fractional-order system. Numerical results demonstrate the chattering-free and effective performance of the proposed control method for uncertain systems in the presence of unknown time-varying external disturbances.