Safe Decision and Control of Connected Automated Vehicles for an Unprotected Left Turn

2020 ◽  
Author(s):  
Sanghoon Oh ◽  
Linjun Zhang ◽  
Eric Tseng ◽  
Wayne Williams ◽  
Helen Kourous ◽  
...  
Keyword(s):  
Decision Making ◽  
Safety Evaluation ◽  
Space Representation ◽  
Potential Conflict ◽  
Efficient Manner ◽  
Left Turn ◽  
The Road ◽  
State Space Representation ◽  
Evaluation Algorithm ◽  
And Control

Abstract The unprotected left turn of a connected automated vehicle (CAV) is investigated when it has a potential conflict with a connected human-driven vehicle (CHV) approaching in the opposite lane. A control architecture is proposed that includes interactions between the decision making, motion planning, and control levels. By utilizing the road context and information received via vehicle-to-everything (V2X) communication, a reduced state space representation is determined which allows the CAV to evaluate safety in a fast and efficient manner Using a temporal metric, a safety evaluation algorithm is developed which determines the safety of the decision making at controller level. To evaluate the algorithms, data collected with real vehicles is utilized.

Modeling, Actuation, and Control of an Active Fluid Vibration Isolator

1997 ◽  
Vol 119 (1) ◽  
pp. 52-59 ◽  
Author(s):  
M. J. Panza ◽  
D. P. McGuire ◽  
P. J. Jones
Keyword(s):  
Electrical Power ◽  
Fluid Pressure ◽  
Space Representation ◽  
Vibration Isolator ◽  
Mass System ◽  
Integral Control ◽  
Active Fluid ◽  
State Space Representation ◽  
In Series ◽  
And Control

An integrated mathematical model for the dynamics, actuation, and control of an active fluid/elastomeric tuned vibration isolator in a two mass system is presented. The derivation is based on the application of physical principles for mechanics, fluid continuity, and electromagnetic circuits. Improvement of the passive isolator performance is obtained with a feedback scheme consisting of a frequency shaped notch compensator in series with integral control of output acceleration and combined with proportional control of the fluid pressure in the isolator. The control is applied via an electromagnetic actuator for excitation of the fluid in the track connecting the two pressure chambers of the isolator. Closed loop system equations are transformed to a nondimensional state space representation and a key dimensionless parameter for isolator-actuator interaction is defined. A numerical example is presented to show the effect of actuator parameter selection on system damping, the performance improvement of the active over the passive isolator, the robustness of the control scheme to parameter variation, and the electrical power requirements for the actuator.

Modeling, Actuation, and Control of an Active Fluid Vibration Isolator

1995 ◽  
Author(s):  
Michael J. Panza ◽  
Dennis P. McGuire ◽  
Peter J. Jones
Keyword(s):  
Electrical Power ◽  
Fluid Pressure ◽  
Space Representation ◽  
Vibration Isolator ◽  
Mass System ◽  
Integral Control ◽  
Active Fluid ◽  
State Space Representation ◽  
In Series ◽  
And Control

Abstract An integrated mathematical model for the dynamics, actuation, and control of an active fluid/elastomeric tuned vibration isolator in a two mass system is presented. The derivation is based on the application of physical principles for mechanics, fluid continuity, and electromagnetic circuits. Improvement of the passive isolator performance is obtained with a feedback scheme consisting of a frequency shaped notch compensator in series with integral control of output acceleration and combined with proportional control of the fluid pressure in the isolator. The control is applied via an electromagnetic actuator for excitation of the fluid in the track connecting the two pressure chambers of the isolator. Closed loop system equations are transformed to a nondimensional state space representation and a key dimensionless parameter for isolator-actuator interaction is defined. A numerical example is presented to show the effect of actuator parameter selection on system damping, the performance improvement of the active over the passive isolator, the robustness of the control scheme to parameter variation, and the electrical power requirements for the actuator.

scholarly journals LINEAR DYNAMIC MATHEMATICAL MODEL AND IDENTIFICATION OF MICRO TURBOJET ENGINE FOR TURBOFAN POWER RATIO CONTROL

Aviation ◽  
2019 ◽  
Vol 23 (2) ◽  
pp. 54-64 ◽  
Author(s):  
Khaoula Derbel ◽  
Károly Beneda
Keyword(s):  
Mathematical Model ◽  
Power Plants ◽  
Space Representation ◽  
Nonlinear Behaviour ◽  
Power Ratio ◽  
Linear Quadratic ◽  
Control Laws ◽  
Turbofan Engines ◽  
State Space Representation ◽  
And Control

Micro turbojets can be used for propulsion of civilian and military aircraft, consequently their investigation and control is essential. Although these power plants exhibit nonlinear behaviour, their control can be based on linearized mathematical models in a narrow neighbourhood of a selected operating point and can be extended by using robust control laws like H∞ or Linear Quadratic Integrating (LQI). The primary aim of the present paper is to develop a novel parametric linear mathematical model based on state space representation for micro turbojet engines and the thrust parameter being Turbofan Power Ratio (TPR). This parameter is used by recent Rolls-Royce commercial turbofan engines but can be applied for single stream turbojet power plants as well, as it has been proven by the authors previously. An additional goal is to perform the identification for a particular type based on measurements of a real engine. This model has been found suitable for automatic control of the selected engine with respect of TPR, this has been validated by simulations conducted in MATLAB® Simulink® environment using acquired data from transient operational modes.

Fractional Optimal Control Within Caputo’s Derivative

2011 ◽  
Author(s):  
Raj Kumar Biswas ◽  
Siddhartha Sen
Keyword(s):  
Optimal Control ◽  
Arbitrary Order ◽  
Numerical Technique ◽  
Space Representation ◽  
Caputo Fractional Derivatives ◽  
Fractional Optimal Control ◽  
State Space Representation ◽  
Dynamic Constraint ◽  
Caputo’S Derivative ◽  
And Control

A general formulation and solution of fractional optimal control problems (FOCPs) in terms of Caputo fractional derivatives (CFDs) of arbitrary order have been considered in this paper. The performance index (PI) of a FOCP is considered as a function of both the state and control. The dynamic constraint is expressed by a fractional differential equation (FDE) of arbitrary order. A general pseudo-state-space representation of the FDE is presented and based on that, FOCP has been developed. A numerical technique based on Gru¨nwald-Letnikov (G-L) approximation of the FDs is used for solving the resulting equations. Numerical example is presented to show the effectiveness of the formulation and solution scheme.

State Space Representation of the Open-Loop Dynamics of the Space Shuttle Main Engine

1991 ◽  
Vol 113 (4) ◽  
pp. 684-690 ◽  
Author(s):  
Ahmet Duyar ◽  
Vasfi Eldem ◽  
Walter C. Merrill ◽  
Ten-Huei Guo
Keyword(s):  
State Space ◽  
Linear Models ◽  
Space Shuttle ◽  
Open Loop ◽  
Space Representation ◽  
Structure Estimation ◽  
State Space Representation ◽  
Loop Dynamics ◽  
Main Engine ◽  
And Control

A parameter and structure estimation technique for multivariable systems is used to obtain state space representation of open loop dynamics of the space shuttle main engine (SSME). The parametrization being used is both minimal and unique. The simplified linear models may be used for fault detection studies and control system design and development.

OPTIMAL CONTROL OF A HYSTERESIS SYSTEM BY MEANS OF CO-OPERATIVE CO-EVOLUTION

2004 ◽  
Vol 04 (04) ◽  
pp. 321-336 ◽  
Author(s):  
KITTIPONG BOONLONG ◽  
NACHOL CHAIYARATANA ◽  
SUWAT KUNTANAPREEDA
Keyword(s):  
Genetic Algorithm ◽  
Optimal Control ◽  
Energy Cost ◽  
Optimal Control Problems ◽  
Hybrid Control ◽  
Space Representation ◽  
Control Problems ◽  
Programming Technique ◽  
Efficient Manner ◽  
State Space Representation

This paper presents the use of a co-operative co-evolutionary genetic algorithm (CCGA) for solving optimal control problems in a hysteresis system. The hysteresis system is a hybrid control system which can be described by a continuous multivalued state-space representation that can switch between two possible discrete modes. The problems investigated cover the optimal control of the hysteresis system with fixed and free final state/time requirements. With the use of the Pontryagin maximum principle, the optimal control problems can be formulated as optimisation problems. In this case, the decision variables consist of the value of control signal when a switch between discrete modes occurs while the objective value is calculated from an energy cost function. The simulation results indicate that the use of the CCGA is proven to be highly efficient in terms of the minimal energy cost obtained in comparison to the results given by the searches using a standard genetic algorithm and a dynamic programming technique. This helps to confirm that the CCGA can handle complex optimal control problems by exploiting a co-evolutionary effect in an efficient manner.

A State-Space Representation Model and Learning Algorithm for Real-Time Decision-Making Under Uncertainty

2007 ◽  
Author(s):  
Andreas A. Malikopoulos ◽  
Panos Y. Papalambros ◽  
Dennis N. Assanis
Keyword(s):  
Decision Making ◽  
Optimal Control ◽  
Real Time ◽  
Learning Algorithm ◽  
Control Policy ◽  
Sequential Decision Making ◽  
Space Representation ◽  
Decision Making Under Uncertainty ◽  
Sequential Decision ◽  
State Space Representation

Modeling dynamic systems incurring stochastic disturbances for deriving a control policy is a ubiquitous task in engineering. However, in some instances obtaining a model of a system may be impractical or impossible. Alternative approaches have been developed using a simulation-based stochastic framework, in which the system interacts with its environment in real time and obtains information that can be processed to produce an optimal control policy. In this context, the problem of developing a policy for controlling the system’s behavior is formulated as a sequential decision-making problem under uncertainty. This paper considers real-time sequential decision-making under uncertainty modeled as a Markov Decision Process (MDP). A state-space representation model is constructed through a learning mechanism and is used to improve system performance over time. The model allows decision making based on gradually enhanced knowledge of system response as it transitions from one state to another, in conjunction with actions taken at each state. A learning algorithm is implemented realizing in real time the optimal control policy associated with the state transitions. The proposed method is demonstrated on the single cart-pole balancing problem and a vehicle cruise control problem.

Simulation and Control of the Vehicles Movement in the Case of the Overtaking Procedures

2014 ◽  
Vol 656 ◽  
pp. 423-431
Author(s):  
Vlad Mureşan ◽  
Adrian Groza ◽  
Bogdan Iancu ◽  
Iulia Clitan
Keyword(s):  
Control Structure ◽  
Simulation System ◽  
Space Representation ◽  
Movement Model ◽  
State Space Representation ◽  
Measured Position ◽  
Simulation And Control ◽  
And Control ◽  
The Mathematical Model ◽  
Vehicle Movement

In this paper, a solution for the simulation and control of the vehicles movement in the case of performing the overtaking procedures is proposed. In order to design the simulation system, the mathematical modeling of the vehicle movement is made, the obtained model being based on the state space representation. Also, the real-time working of the simulator is based both on the information obtained through the usage of a communication network between the vehicles and of the GPS-measured position. The main advantage of the proposed system consists in assisting the driver to perform a correct and a safe overtaking. Another original element presented in this paper is the including of the vehicle movement model in a control structure, resulting the possibility that the overtaking to be performed with a higher efficiency. The mathematical model, respectively the simulation system were tested and validated through some simulations associated to an overtaking scenario, simulations presented in this paper, too.

scholarly journals LMI–Based Robust Control of Uncertain Nonlinear Systems via Polytopes of Polynomials

2019 ◽  
Vol 29 (2) ◽  
pp. 275-283 ◽  
Author(s):  
Marcelino Sánchez ◽  
Miguel Bernal
Keyword(s):  
Nonlinear Systems ◽  
Space Representation ◽  
Linear Matrix ◽  
Uncertain Nonlinear Systems ◽  
Linear Parameter Varying ◽  
Analysis And Design ◽  
Linear Parameter Varying Systems ◽  
State Space Representation ◽  
The Subject ◽  
And Control

Abstract This investigation is concerned with robust analysis and control of uncertain nonlinear systems with parametric uncertainties. In contrast to the methodologies from the field of linear parameter varying systems, which employ convex structures of the state space representation in order to perform analysis and design, the proposed approach makes use of a polytopic form of a generalisation of the characteristic polynomial, which proves to outperform former results on the subject. Moreover, the derived conditions have the advantage of being cast as linear matrix inequalities under mild assumptions.

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