Unknown Environmental Disturbances Research Articles

Event-Triggered Controller Design for Autopilot with Input Saturation

This paper considers the problem of autopilot design for surface ship with environmental disturbances and input saturation. Extended state observer (ESO) is used to reconstruct yaw rate and estimate unknown environmental disturbances. An auxiliary dynamic system is employed to handle the input saturation. By combining with the auxiliary dynamic system and ESO, an event-triggered controller (ETC) is designed, and energy is saved by reduction in the rudder rate. Simulation results illustrate the effectiveness and feasibility of the event-triggered proposed controller.

Observer-Based Neural Formation Control of Leader–Follower AUVs With Input Saturation

This article investigates the three-dimensional formation tracking control problem of leader–follower autonomous underwater vehicles with input saturation under uncertain nonlinearities. For this purpose, a saturated formation tracking controller is developed by using the generalized saturation functions. This technique can effectively prevent actuators saturation and improve the transient performance of the presented control system. A nonlinear velocity observer is also designed to estimate the velocity signals of followers. Then, an estimation model based on the neural adaptive robust techniques is proposed to deal with the uncertain nonlinearities, such as unknown model dynamics, environmental disturbances, and approximation errors. A Lyapunov-based stability analysis is provided to guarantee that all signals of the closed-loop system are uniformly ultimately bounded. Finally, the reliability and robustness of the presented controller are demonstrated through simulations.

Partial attitude stabilization underactuated control with disturbance observers for post-captured space robot

In this study, a takeover controller is proposed for a post-captured space robot with the underactuated property under the effect of unknown environmental disturbances and the gravitational gradient moment. The (w, z) parameter is introduced to describe the attitude, and an extended kinematics is derived by the additional consideration of the orbital motion of the space robot. To eliminate the effect of disturbances on the underactuated axis, two disturbance observers is proposed for the actuated axes and underactuated axis. Based on the extended kinematics and the observers, a kinematic controller is applied to stabilize the attitude. Moreover, a dynamic controller is derived to achieve the partial stabilization of the post-captured space robot around the specific axis. The convergences of the controllers are proven. The simulation results show that the state variables converge to demand values, and the angular velocity of the underactuated axis maintains at a constant value.

Adaptive sliding mode output feedback control for dynamic positioning ships with input saturation

In this paper, a finite-time observer-based adaptive sliding mode output feedback controller is developed for dynamic positioning ship while the Coriolis matrix, hydrodynamic nonlinear damping matrix, input saturation, unmeasured states, unknown time-varying environment disturbances and transient performance are considered simultaneously. A continue finite-time state observer is proposed to estimate the unmeasured states of dynamic positioning ship in finite time and an auxiliary system is constructed to handle with the control saturation. A terminal sliding mode surface with the signal generated by the auxiliary system is designed while the good transient performance is achieved under multiple constraints and the nominal output feedback controller proposed in this paper is chatter-free guaranteeing the steady performance. In additional, an adaptive update law is introduced that the prior knowledge of disturbance is no need and the finite-time convergence of loop-system is proved strictly. Finally, simulations are given to illustrate the effectiveness and advantages of the proposed control scheme.

Adaptive Self-Regulation PID Control of Course-Keeping for Ships

Abstract To solve the nonlinear control problems of the unknown time-varying environmental disturbances and parametric uncertainties for ship course-keeping control, this paper presents an adaptive self-regulation PID (APID) scheme which can ensure the boundedness of all signals in the ship course-keeping control system by using the Lyapunov direct method. Compared with the traditional PID control scheme, the APID control scheme not only is independent of the model parameters and the unknown input, but also can regulate the gain of PID adaptively and resist time-varying disturbances well. Simulation results illustrate the effectiveness and the robustness of the proposed control scheme.

Cooperative Control for Multirotors Transporting an Unknown Suspended Load Under Environmental Disturbances

In this paper, we develop a cooperative control algorithm for a group of multirotor unmanned aerial vehicles (UAVs) transporting a suspended payload of unknown mass. In addition, the vehicles are subjected to unknown environmental disturbances in the form of wind. The control structure is analyzed using Lyapunov theory, and both numerical simulations and results from experimental field trials on an outdoor multirotor platform further validate the proposed control algorithm.

Bottom-Following Control of Underactuated Unmanned Undersea Vehicles With Input Saturation

This article addresses the subject for bottom-following control of underactuated unmanned undersea vehicles (UUVs) with input saturation in the presence of unknown model uncertainties and unknown external disturbances. A robust adaptive dynamic surface bottom-following control scheme is developed based on the recursive sliding mode with nonlinear gains and neural networks, which can steer an underactuated UUV to precisely follow the bottom profile at a constant altitude as a basic feature. The bottom-following guidance law is derived based on the Serret-Frenet frame, the line of sight (LOS) and Lyapunov's direct technique. Then, the bottom-following controller is designed based on the recursive sliding mode and dynamic surface control (DSC), to stabilize the bottom-following errors. The radial basis function neural networks (RBF NNs) are employed to online approximate the uncertain dynamics of underactuated UUVs, while the adaptive laws are introduced to estimate the bounds of the RBF NN approximation errors and unknown environmental disturbances. Additionally, an auxiliary dynamic system (ADS) is presented to handle the effect of input saturation. The uniform boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis. The simulation results are presented to verify and illustrate the effectiveness of the proposed control scheme.

Adaptive compound second-order terminal sliding mode control for the longitudinal attitude control of the fully submerged hydrofoil vessel

Due to the ever-existing environmental disturbance of ocean wave and nonlinear of the system, it is difficult to obtain a satisfying control performance for the longitudinal attitude and desired height tracking of the fully submerged hydrofoil vessel. To solve such problems, an adaptive compound second-order terminal sliding mode controller is proposed. First, a combination of the complementary sliding mode surface and second-order terminal sliding mode control is introduced. Therefore, the closed system is uniformly ultimately bounded, and the steady-state errors converge to a small neighborhood of equilibrium point. Second, the chattering problem in an actual controller is solved by eliminating the sign function contained in the controller after integration without influencing the stability of the closed-loop system. Besides, a revised adaptive radial basis function neural network is introduced to estimate the derivative of the unknown environmental disturbances without the prior information of the disturbance. Finally, the stability of the system is proved by the Lyapunov stability theory. Numerical experimental results demonstrate that the proposed method possesses fast tracking ability and can decrease the stabilization error and the tracking error simultaneously.

Improved Integral LOS Guidance and Path-Following Control for an Unmanned Robot Sailboat via the Robust Neural Damping Technique

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

Improved adaptive integral line-of-sight guidance law and adaptive fuzzy path following control for underactuated MSV

This paper presents an adaptive fuzzy path following control law based on an improved adaptive integral line-of-sight (IAILOS) guidance law for the underactuated marine surface vessel (MSV) exposed to the time-varying ocean currents and time-varying sideslip angle. Initially, the IAILOS guidance law is proposed which can not only calculate the desired yaw angle but also estimate the time-varying ocean currents and time-varying sideslip angle simultaneously. Furthermore, the adaptive fuzzy path following control law is established by combining with the estimator to cope with the MSV’s attitude tracking control and velocity tracing control problem via backstepping technique. Specifically, the dynamic uncertainties and unknown environment disturbances are compensated by the fuzzy logic system with fuzzy updating law based on estimation error rather than tracking error. Additionally, two high-order tracking differentiators (TDs) are designed to construct derivatives of virtual control vector and reduce computational complexity inherent in backstepping method. It is proved that the proposed adaptive fuzzy path following control law can drive the vessel to track the desired path and tracking error can converge to an arbitrarily small compact set, while guaranteeing all signals in the closed-loop control system are uniformly ultimately bounded. Finally, simulation results and comparisons are carried out to demonstrate the effectiveness of the proposed control approach.

High-Gain Observer-Based Neural Adaptive Feedback Linearizing Control of a Team of Wheeled Mobile Robots

SummaryThis paper addresses the neural network (NN) output feedback formation tracking control of nonholonomic wheeled mobile robots (WMRs) with limited voltage input. A desired formation is achieved based on the leader–follower strategy utilizing hyperbolic tangent saturation functions to reduce the risk of actuator saturation. The controller is developed by incorporating the high-gain observer and radial basis function (RBF) NNs using the inverse dynamics control technique. The high-gain observer is introduced to estimate velocities of the followers. The RBF NN preserves the robustness of the proposed controller against uncertain nonlinearities. The adaptive laws are also combined by a robust control term to estimate the weights of RBF NN, approximation errors, and bounds of unknown time-variant environmental disturbances. A Lyapunov-based stability analysis proves that all signals of the closed-loop system are bounded, and tracking errors are uniformly ultimately bounded. Finally, some simulations are carried out to show the effectiveness of the proposed controller for a number of WMRs.

Cooperative Control of Multiple Dynamic Positioning Vessels with Input Saturation Based on Finite-time Disturbance Observer

This paper presents a new cooperative control strategy for dynamic positioning of multiple surface vessels subject to unknown time-varying environmental disturbances and input saturation. The vessels are assumed interconnected through a directed topology rather than bidirectional. Two control objectives are considered in this paper. The first one is to make these vessels track desired positions and headings, and the other control objective is to hold the desired formation. For these purposes, we propose a cooperative control which consists of finite-time disturbance observer, auxiliary dynamic system and dynamic surface control technique. A nonlinear finite-time observer is developed to estimate unknown time-varying disturbance. To tackle the input saturation problem, an auxiliary dynamic system is constructed. It is also proved that all signals in the closed-loop control system converge to a small neighborhood of equilibrium state via Lyapunov analysis. Simulation results are given to validate the effectiveness of the proposed control strategy.

High-Gain Observer-Based Line-of-Sight Guidance for Adaptive Neural Path Following Control of Underactuated Marine Surface Vessels

This paper presents an adaptive neural network dynamic surface control law with time-varying sideslip compensation, which includes a geometric kinematic control design and a dynamic control design, for path following of underactuated marine surface vessels (MSVs) in the presence of unmeasured states, model uncertainties, unknown ocean environmental disturbances, and input saturation. First, a high gain observer based line-of-sight guidance law, capable of estimating and compensating the time-varying sideslip angle induced by the unknown time-varying ocean disturbances, is proposed to generate the desired heading for the dynamic control system of the MSV. Next, considering the input saturation, adaptive neural network dynamic surface velocity control laws, in which the model uncertainties and unknown ocean environmental disturbances of the system are compensated by adaptive radial basis function neural network and the problem of input saturation is solved by introducing auxiliary dynamic systems, are designed to realize the dynamic control target of the path following. The proposed control strategy of path following compensates the ocean environmental disturbances from the perspective of both the geometric kinematics and the dynamics, and all error signals of a closed-loop control system are proven to be uniformly ultimately bounded. The simulations validate the effectiveness of the proposed control strategy for path following of MSVs.

A Finite-Time Output Feedback Control Scheme for Dynamic Positioning System of Ships

This paper develops a finite-time output feedback control scheme for dynamic positioning (DP) system of ships in the presence of unmeasured states of ships, unknown dynamic model parameters and unknown time-varying environment disturbances. A novel finite-time extended state observer (FTESO) is first proposed to simultaneously and precisely estimate the unmeasured states of ships, unknown dynamic model parameters, and unknown time-varying environment disturbances in finite time. Second, based on the outputs of FTESO, the terminal sliding mode (TSM) controller is designed to guarantee that the DP system can track the position and heading at desired values in finite time with precise performance. Then, it is proved that all error signals of the closed-loop DP control system can converge to zero in finite time by utilizing the homogeneous method and the Lyapunov stability theory. Finally, the numerical simulations on a supply ship are carried out to illustrate the effectiveness of the proposed finite-time output feedback control scheme.

Neuroadaptive Distributed Output Feedback Tracking Control for Multiple Marine Surface Vessels With Input and Output Constraints

In this paper, a neuroadaptive distributed output feedback formation tracking control scheme for multiple marine surface vessels with model uncertainties, unknown environmental disturbances and input and output constraints is proposed. A neural network based observer is developed to reconstruct the unmeasured velocity and approach the model uncertainties. To handle the input constraint, an auxiliary dynamic system is introduced. The tracking error transformation and the barrier Lyapunov function are used to tackle with the output constraint. Subsequently, by using the estimated velocity of neighboring vessels, neuroadaptive distributed output feedback controllers are developed. Furthermore, to avoid directly taking the time derivation of virtual control law and generate smooth reference signals, linear tracking differentiators are employed. Finally, it is shown that all the signals in the closed-loop system are bounded via Lyapunov analysis. Simulations are carried out to verify the proposed control scheme.

Output-Feedback Control for Cooperative Diving of Saucer-Type Underwater Gliders Based on a Fuzzy Observer and Event-Triggered Communication

This paper presents an output-feedback control method for cooperative diving of multiple homogenous under-actuated saucer-type autonomous underwater gliders (AUGs) subjected to unmeasured velocities, model uncertainties, as well as unknown environmental disturbances. A robust cooperative diving controller is constructed by using a modular back-stepping design method. First, a fuzzy observer combined with a low-frequency learning scheme is presented to identify the unknown AUG dynamics as well as to estimate the unmeasured velocities. Second, a commanded guidance law is designed based on the observed velocities and a vertical line-of-sight guidance scheme at the kinematic level, and fuzzy dynamic control law is developed at the kinetic level. Finally, a non-periodic path update law based on an event-triggered mechanism is designed to reduce the communication frequency. By using the cascade theory, the stability of the closed-loop system is analyzed. The simulation results are provided to show the effectiveness of the proposed output-feedback control approach for saucer-type AUGs.

Deep reinforcement learning-based path planning of underactuated surface vessels

ABSTRACTThis paper is dedicated to the issues of path planning for the underactuated surface vessel (USV) in unknown environments with obstacles. Aiming at the usability problem caused by the complicated control law of the traditional method, a deep deterministic policy gradient (DDPG)-based path planning algorithm is proposed with the powerful actor-critic architecture. The main contributions of this paper are as follows: (1) The DDPG-based path planning method is the decision control system of USV whose output is continuous. (2) A complete reward system is specially designed for target approaching, speed control and attitude correction. (3) Since the reward system is independent, it is highly customisable and can be changed according to the task and the control model. Through the simulation, the results show that the perfect path can be automatically generated under unknown environmental disturbance, thus providing the proposed DDPG-based path planning scheme effectiveness and applied meaning.

Output Feedback Thruster Fault-Tolerant Control for Dynamic Positioning of Vessels Under Input Saturation

In this paper, an output feedback fault-tolerant control (FTC) scheme is presented for the dynamic positioning of vessels subjected to external disturbances, dynamic uncertainties, and thruster saturation constraints under thruster faults. A high-gain observer is constructed to acquire the estimates of vessel velocities. An auxiliary dynamic system is introduced to compensate the effect of the thruster faults and saturation constrains. Neural network with iterative updating laws is employed to approximate the lumped uncertainties caused by unknown environmental disturbances and dynamic uncertainties of vessels. Furthermore, the control allocation is accomplished to distribute the FTC forces and moment among individual thrusters. It is theoretically proved that the derived FTC scheme has the capability to maintain the vessel position at the desired values and guarantees that all signals in the closed-loop control system are uniformly ultimately bounded. Finally, the simulation results demonstrate the effectiveness of the proposed control scheme.

Reliability-Based Robust Online Constructive Fuzzy Positioning Control of a Turret-Moored Floating Production Storage and Offloading Vessel

In this paper, a mathematical model for a floating production storage and offloading (FPSO) vessel is introduced at first. Considering the unknown system parameters and environmental disturbances, we proposed a reliability-based robust online constructive fuzzy controller. An online constructive scheme is constructed to ensure the fuzzy system’s fuzzy rules adequate and parsimonious without any prior knowledge about the number of fuzzy rules and the structure of fuzzy system. In addition, the reliability-based matrix is applied to design a new adaptive fuzzy parameter update law which can not only approximate the unknown term containing the non-square reliability-based matrix but also make it possible to analyze the closed-loop system’s stability, which is quite difficult to be analyzed because the reliability-based matrix is non-square. Our proposed online constructive fuzzy controller can not only maintain the FPSO vessel at the desired reliability and heading but also ensure all signals in the closed-loop control system are bounded. Simulations and comparisons with a reliability-based structure-fixed fuzzy controller show our proposed reliability-based online constructive fuzzy controller can achieve the positioning control by using the fuzzy approximator with adequate and parsimonious fuzzy rules.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method.