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.

Flight Control System Design for Propulsion-Controlled Aircraft

2005 ◽  
Vol 219 (4) ◽  
pp. 329-340 ◽  
Author(s):  
Y Ochi
Keyword(s):  
Flight Control ◽  
Linear Models ◽  
Control Method ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Longitudinal Motion ◽  
Linear Quadratic ◽  
Engine Thrust ◽  
Model Following Control ◽  
Flight Controls

The loss of an aircraft's primary flight controls can lead to a fatal accident. However, if the engine thrust is available, controllability and safety can be retained. This article describes flight control using engine thrust only when an aircraft has lost all primary flight controls. This is a kind of flight control reconfiguration. For safe return, the aircraft must first descend to a landing area, decelerate to a landing speed, and then be capable of precise flight control for approach and landing. For these purposes, two kinds of controllers are required: a controller for descent and deceleration and a controller for approach and landing. The former controller is designed for longitudinal motion using a model-following control method, based on a linear quadratic regulator. The latter is designed by an H∞ state-feedback control method for both longitudinal and lateral-directional motions. Computer simulation is conducted using linear models of the Boeing 747. The results indicate that flight path control, including approach and landing, is possible using thrust only; however, speed control proves more difficult. However, if the horizontal stabilizer is available, the airspeed can be reduced to a safe landing speed.

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.

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.  

scholarly journals Feedback Control Methods for a Single Machine Infinite Bus System

2020 ◽  
Author(s):  
Pratik Vernekar ◽  
Zhongkui Wang ◽  
Andrea Serrani ◽  
Kevin Passino
Keyword(s):  
Single Machine ◽  
Linear Models ◽  
Linear Quadratic Regulator ◽  
Pole Placement ◽  
High Fidelity ◽  
Nonlinear Feedback ◽  
Linear Quadratic ◽  
Reduced Order ◽  
System P ◽  
Single Machine Infinite Bus

In this manuscript, we present a high-fidelity physics-based truth model of a Single Machine Infinite Bus (SMIB) system. We also present reduced-order control-oriented nonlinear and linear models of a synchronous generator-turbine system connected to a power grid. The reduced-order control-oriented models are next used to design various control strategies such as: proportional-integral-derivative (PID), linear-quadratic regulator (LQR), pole placement-based state feedback, observer-based output feedback, loop transfer recovery (LTR)-based linear-quadratic-Gaussian (LQG), and nonlinear feedback-linearizing control for the SMIB system. The controllers developed are then validated on the high-fidelity physics-based truth model of the SMIB system. Finally, a comparison is made of the performance of the controllers at different operating points of the SMIB system.

scholarly journals Feedback Control Methods for a Single Machine Infinite Bus System

2020 ◽  
Author(s):  
Pratik N Vernekar ◽  
Zhongkui Wang ◽  
Andrea Serrani ◽  
Kevin Passino
Keyword(s):  
Single Machine ◽  
Linear Models ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Pole Placement ◽  
High Fidelity ◽  
Nonlinear Feedback ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Single Machine Infinite Bus

Abstract In this manuscript, we present a high-fidelity physics-based truth model of a Single Machine Infinite Bus (SMIB) system. We also present reduced-order control-oriented nonlinear and linear models of a synchronous generator-turbine system connected to a power grid. The reduced-order control-oriented models are next used to design various control strategies such as: proportional-integral-derivative (PID), linear-quadratic regulator (LQR), pole placement-based state feedback, observer-based output feedback, loop transfer recovery (LTR)-based linear-quadratic-Gaussian (LQG), and nonlinear feedback-linearizing control for the SMIB system. The controllers developed are then validated on the high-fidelity physics-based truth model of the SMIB system. Finally, a comparison is made of the performance of the controllers at different operating points of the SMIB system.

scholarly journals Feedback Control Methods for a Single Machine Infinite Bus System

2020 ◽  
Author(s):  
Pratik N Vernekar ◽  
Zhongkui Wang ◽  
Andrea Serrani ◽  
Kevin Passino
Keyword(s):  
Single Machine ◽  
Linear Models ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Synchronous Generator ◽  
Pole Placement ◽  
Nonlinear Feedback ◽  
Linear Quadratic ◽  
Reduced Order ◽  
Single Machine Infinite Bus

Abstract In this manuscript we present a high fidelity physics-based truth model of a Single Machine Infinite Bus (SMIB) system. We also present reduced-order control-oriented nonlinear and linear models of a synchronous generator-turbine system connected to a power grid. The reduced-order control-oriented models are next used to design various control strategies such as: proportional-integral-derivative (PID), linear-quadratic regulator (LQR), pole placement-based state feedback, observer-based output feedback, loop transfer recovery (LTR)-based linear-quadratic-Gaussian (LQG), and nonlinear feedback-linearizing control for the SMIB system. The controllers developed are then validated on the higher fidelity physics-based truth model of the SMIB system. Finally, a comparison is made of the performance of the controllers at different operating points of the SMIB system.

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