EXPERIMENTAL ANALYSIS OF HOMEOSTATIC-INSPIRED MOTION CONTROLLER FOR A HYBRID-DRIVEN AUTONOMOUS UNDERWATER GLIDER

2015 ◽  
Vol 74 (9) ◽  
Author(s):  
Khalid Isa ◽  
M. R. Arshad
Keyword(s):  
Predictive Control ◽  
Stable State ◽  
Linear Quadratic Regulator ◽  
Water Current ◽  
Underwater Glider ◽  
Motion Controller ◽  
Linear Quadratic ◽  
Controller Performance ◽  
The Face ◽  
Autonomous Underwater Glider

This paper presents a homeostatic controller algorithm and its performance, which controls motion of a hybrid-driven underwater glider. The homeostatic controller is inspired from a biological process known as homeostasis, which maintains a stable state in the face of massively dynamics conditions. The objective is to obtain a better control performance of the glider motion control system with a presence of disturbance, which is the water current. The algorithm was simulated by using MatlabTM. According to the simulation results, in order to achieve the desired pitch angle, the homeostatic controller was able to optimize the glider’s ballast mass and distance of the glider’s sliding mass by reducing the ballast mass up to 17.7% and shortening the sliding mass distance up to 53.7% when compared with the linear-quadratic regulator (LQR) and model predictive control (MPC). Furthermore, validation analyses of the homeostatic controller performance between the simulation and experimental results have shown very satisfactory performance.  

EFFECT OF WATER CURRENT ON UNDERWATER GLIDER VELOCITY AND RANGE

2016 ◽  
Vol 78 (10-4) ◽  
Author(s):  
Muhammad Yasar Javaid ◽  
Mark Ovinis ◽  
Fakhruldin Mohd Hashim ◽  
Adi Maimun ◽  
Yasser M. Ahmed ◽  
...  
Keyword(s):  
Steady State ◽  
Numerical Simulations ◽  
Relative Motion ◽  
Water Current ◽  
Underwater Glider ◽  
Water Currents ◽  
Effect Of Water ◽  
Actuation System ◽  
Autonomous Underwater Glider

An autonomous underwater glider speed and range is influenced by water currents. This is compounded by a weak actuation system for controlling its movement. In this work, the effects of water currents on the speed and range of an underwater glider at steady state glide conditions are investigated. Extensive numerical simulations have been performed to determine the speed and range of a glider with and without water current at different net buoyancies. The results show that the effect of water current on the glider speed and range depends on the current relative motion and direction. In the presence of water current, for a given glide angle, glide speed can be increased by increasing the net buoyancy of the glider.

scholarly journals Optimal Attack against Autoregressive Models by Manipulating the Environment

2020 ◽  
Vol 34 (04) ◽  
pp. 3545-3552
Author(s):  
Yiding Chen ◽  
Xiaojin Zhu
Keyword(s):  
Predictive Control ◽  
Linear Models ◽  
Nonlinear Models ◽  
Linear Quadratic Regulator ◽  
Black Box ◽  
Combine System ◽  
Linear Quadratic ◽  
Time Series Forecast ◽  
Forecast Models ◽  
Adversarial Attack

We describe an optimal adversarial attack formulation against autoregressive time series forecast using Linear Quadratic Regulator (LQR). In this threat model, the environment evolves according to a dynamical system; an autoregressive model observes the current environment state and predicts its future values; an attacker has the ability to modify the environment state in order to manipulate future autoregressive forecasts. The attacker's goal is to force autoregressive forecasts into tracking a target trajectory while minimizing its attack expenditure. In the white-box setting where the attacker knows the environment and forecast models, we present the optimal attack using LQR for linear models, and Model Predictive Control (MPC) for nonlinear models. In the black-box setting, we combine system identification and MPC. Experiments demonstrate the effectiveness of our attacks.

scholarly journals Trajectory Tracking and Stabilization of a Quadrotor Using Model Predictive Control of Laguerre Functions

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Mapopa Chipofya ◽  
Deok Jin Lee ◽  
Kil To Chong
Keyword(s):  
State Space ◽  
Predictive Control ◽  
Trajectory Tracking ◽  
Linear Quadratic Regulator ◽  
Laguerre Functions ◽  
Linear Quadratic ◽  
Model Predictive Controller ◽  
Predictive Controller ◽  
Linear State ◽  
Quadrotor System

This paper presents a solution to stability and trajectory tracking of a quadrotor system using a model predictive controller designed using a type of orthonormal functions called Laguerre functions. A linear model of the quadrotor is derived and used. To check the performance of the controller we compare it with a linear quadratic regulator and a more traditional linear state space MPC. Simulations for trajectory tracking and stability are performed in MATLAB and results provided in this paper.

Pitch and Depth Control of Underwater Glider using LQG and LQR via Kalman Filter

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
B. Ullah ◽  
M. Ovinis ◽  
M.B. Baharom ◽  
S.S.A Ali ◽  
M.Y. Javaid
Keyword(s):  
Kalman Filter ◽  
Linear Quadratic Regulator ◽  
Good Control ◽  
External Noise ◽  
Control Surface ◽  
Underwater Glider ◽  
Linear Quadratic ◽  
Control Effort ◽  
Underwater Gliders ◽  
Depth Control

Underwater gliders are adversely affected by ocean currents because of their low speed, which is compounded by an inability to make quick corrective manoeuvres due to limited control surface and weak buoyancy driven propulsion system. In this paper, Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) robust controllers are presented for pitch and depth control of an underwater glider. The LQR and LQG robust control schemes are implemented using MATLAB/Simulink. A Kalman filter was designed to estimate the pitch of the glider. Based on the simulation results, both controllers are compared to show the robustness in the presence of noise. The LQG controller results shows good control effort in presence of external noise and the stability of the controller performance is guaranteed.

scholarly journals 3-Dimensional Modeling and Attitude Control of Multi-Joint Autonomous Underwater Vehicles

2021 ◽  
Vol 9 (3) ◽  
pp. 307
Author(s):  
Lin Yu ◽  
Qinghao Meng ◽  
Hongwei Zhang
Keyword(s):  
Attitude Control ◽  
Autonomous Underwater Vehicle ◽  
Control Method ◽  
Autonomous Underwater Vehicles ◽  
Stable State ◽  
Linear Quadratic Regulator ◽  
Linear Quadratic ◽  
Controlled System ◽  
3 Dimensional ◽  
Yaw Attitude

To achieve rapid and flexible vertical profile exploration of deep-sea hybrid structures, a multi-joint autonomous underwater vehicle (MJ-AUV) with orthogonal joints was designed. This paper focuses on the 3-dimensional (3D) modeling and attitude control of the designed vehicle. Considering the situation of gravity and buoyancy imbalance, a 3D model of the MJ-AUV was established according to Newton’s second law and torque balance principle. And then the numerical simulation was carried out to verify the credibility of the model. To solve the problems that the pitch and yaw attitude of the MJ-AUV are coupled and the disturbance is unknown, a linear quadratic regulator (LQR) decoupling control method based on a linear extended state observer (LESO) was proposed. The system was decoupled into pitch and yaw subsystems, treated the internal forces and external disturbances of each subsystem as total disturbances, and estimated the total disturbances with LESO. The control law was divided into two parts. The first part was the total disturbance compensator, while the second part was the linear state feedback controller. The simulation results show that the overshoot of the controlled system in the dynamic process is nearly 0 rad, reaching the design value very smoothly. Moreover, when the controlled system is in a stable state, the control precision is within 0.005%.

scholarly journals An Online Iterative Linear Quadratic Approach for a Satisfactory Working Point Attainment at FERMI

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 262
Author(s):  
Niky Bruchon ◽  
Gianfranco Fenu ◽  
Giulio Gaio ◽  
Simon Hirlander ◽  
Marco Lonza ◽  
...  
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Free Electron ◽  
Free Electron Laser ◽  
Model Identification ◽  
Linear Quadratic Regulator ◽  
Particle Accelerators ◽  
Linear Quadratic ◽  
Model Accuracy ◽  
The Neural Network

The attainment of a satisfactory operating point is one of the main problems in the tuning of particle accelerators. These are extremely complex facilities, characterized by the absence of a model that accurately describes their dynamics, and by an often persistent noise which, along with machine drifts, affects their behaviour in unpredictable ways. In this paper, we propose an online iterative Linear Quadratic Regulator (iLQR) approach to tackle this problem on the FERMI free-electron laser of Elettra Sincrotrone Trieste. It consists of a model identification performed by a neural network trained on data collected from the real facility, followed by the application of the iLQR in a Model-Predictive Control fashion. We perform several experiments, training the neural network with increasing amount of data, in order to understand what level of model accuracy is needed to accomplish the task. We empirically show that the online iLQR results, on average, in fewer steps than a simple gradient ascent (GA), and requires a less accurate neural network to achieve the goal.

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