1,439 research outputs found
Formation of Spherical D2-brane from Multiple D0-branes
We study D-branes in SU(2) WZW model by means of the boundary state
techniques. We realize the ``fuzzy sphere'' configuration of multiple D0-branes
as the boundary state with the insertion of suitable Wilson line. By making use
of the path-integral representation we show that this boundary state preserves
the appropriate boundary conditions and leads to the Cardy state describing a
spherical D2-brane under the semi-classical approximation. This result directly
implies that the spherical D2-brane in SU(2) WZW model can be well described as
the bound state of D0-branes.
After presenting the supersymmetric extension, we also investigate the BPS
and the non-BPS configurations of D-branes in the NS5 background. We
demonstrate that the non-BPS configurations are actually unstable, since they
always possess the open string tachyons. We further notice that the stable BPS
bound state constructed by the tachyon condensation is naturally interpreted as
the brane configuration of fuzzy sphere.Comment: 36 pages, no figure, v2: typos corrected, references added, v3: minor
corrections, some discussions added in Sec. 2, v4: references added, v5:
appendix added, accepted for publication in Nuclear Physics
Adaptive Control
Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems
Sensitivity Study of a Class of Fuzzy Control Systems
The paper performs the sensitivity study with respect to the parametric
variations of the controlled plant in case of a class of fuzzy control
systems dedicated to servo systems. The presentation is particularized to
fuzzy control systems to solve the tracking control problem in case of
wheeled mobile robots of tricycle type with two degrees of freedom. There is
proposed a new development method for Takagi-Sugeno PI-fuzzy controllers
based on the application of the Extended Symmetrical Optimum method to the
basic linear PI controllers in a cascaded control system structure. There
are derived sensitivity models, validated by considering a case study
concerning the speed control of a servo system with DC motor as actuator in
mobile robot control. Experimental results validate the development method
for Takagi-Sugeno PI-fuzzy controllers
Near-Optimal Control of a Quadcopter Using Reinforcement Learning
This paper presents a novel control method for quadcopters that achieves near-optimal tracking control for input-affine nonlinear quadcopter dynamics. The method uses a reinforcement learning algorithm called Single Network Adaptive Critics (SNAC), which approximates a solution to the discrete-time Hamilton-Jacobi-Bellman (DT-HJB) equation using a single neural network trained offline. The control method involves two SNAC controllers, with the outer loop controlling the linear position and velocities (position control) and the inner loop controlling the angular position and velocities (attitude control). The resulting quadcopter controller provides optimal feedback control and tracks a trajectory for an infinite-horizon, and it is compared with commercial optimal control software. Furthermore, the closed-loop controller can control the system with any initial conditions within the domain of training. Overall, this research demonstrates the benefits of using SNAC for nonlinear control, showing its ability to achieve near-optimal tracking control while reducing computational complexity. This paper provides insights into a new approach for controlling quadcopters, with potential applications in various fields such as aerial surveillance, delivery, and search and rescue
A Human Driver Model for Autonomous Lane Changing in Highways: Predictive Fuzzy Markov Game Driving Strategy
This study presents an integrated hybrid solution to mandatory lane changing problem
to deal with accident avoidance by choosing a safe gap in highway driving. To manage
this, a comprehensive treatment to a lane change active safety design is proposed from
dynamics, control, and decision making aspects.
My effort first goes on driver behaviors and relating human reasoning of threat in
driving for modeling a decision making strategy. It consists of two main parts; threat assessment
in traffic participants, (TV s) states, and decision making. The first part utilizes
an complementary threat assessment of TV s, relative to the subject vehicle, SV , by evaluating
the traffic quantities. Then I propose a decision strategy, which is based on Markov
decision processes (MDPs) that abstract the traffic environment with a set of actions, transition
probabilities, and corresponding utility rewards. Further, the interactions of the TV s
are employed to set up a real traffic condition by using game theoretic approach. The question
to be addressed here is that how an autonomous vehicle optimally interacts with the
surrounding vehicles for a gap selection so that more effective performance of the overall
traffic flow can be captured. Finding a safe gap is performed via maximizing an objective
function among several candidates. A future prediction engine thus is embedded in the
design, which simulates and seeks for a solution such that the objective function is maximized
at each time step over a horizon. The combined system therefore forms a predictive
fuzzy Markov game (FMG) since it is to perform a predictive interactive driving strategy
to avoid accidents for a given traffic environment. I show the effect of interactions in decision
making process by proposing both cooperative and non-cooperative Markov game
strategies for enhanced traffic safety and mobility. This level is called the higher level
controller. I further focus on generating a driver controller to complement the automated
car’s safe driving. To compute this, model predictive controller (MPC) is utilized. The
success of the combined decision process and trajectory generation is evaluated with a set
of different traffic scenarios in dSPACE virtual driving environment.
Next, I consider designing an active front steering (AFS) and direct yaw moment control
(DYC) as the lower level controller that performs a lane change task with enhanced
handling performance in the presence of varying front and rear cornering stiffnesses. I propose
a new control scheme that integrates active front steering and the direct yaw moment
control to enhance the vehicle handling and stability. I obtain the nonlinear tire forces
with Pacejka model, and convert the nonlinear tire stiffnesses to parameter space to design
a linear parameter varying controller (LPV) for combined AFS and DYC to perform a
commanded lane change task. Further, the nonlinear vehicle lateral dynamics is modeled
with Takagi-Sugeno (T-S) framework. A state-feedback fuzzy H∞ controller is designed
for both stability and tracking reference. Simulation study confirms that the performance
of the proposed methods is quite satisfactory
Systems Structure and Control
The title of the book System, Structure and Control encompasses broad field of theory and applications of many different control approaches applied on different classes of dynamic systems. Output and state feedback control include among others robust control, optimal control or intelligent control methods such as fuzzy or neural network approach, dynamic systems are e.g. linear or nonlinear with or without time delay, fixed or uncertain, onedimensional or multidimensional. The applications cover all branches of human activities including any kind of industry, economics, biology, social sciences etc
STABILITY AND PERFORMANCE OF NETWORKED CONTROL SYSTEMS
Network control systems (NCSs), as one of the most active research areas, are arousing comprehensive concerns along with the rapid development of network. This dissertation mainly discusses the stability and performance of NCSs into the following two parts.
In the first part, a new approach is proposed to reduce the data transmitted in networked control systems (NCSs) via model reduction method. Up to our best knowledge, we are the first to propose this new approach in the scientific and engineering society. The "unimportant" information of system states vector is truncated by balanced truncation method (BTM) before sending to the networked controller via network based on the balance property of the remote controlled plant controllability and observability. Then, the exponential stability condition of the truncated NCSs is derived via linear matrix inequality (LMI) forms. This method of data truncation can usually reduce the time delay and further improve the performance of the NCSs. In addition, all the above results are extended to the switched NCSs.
The second part presents a new robust sliding mode control (SMC) method for general uncertain time-varying delay stochastic systems with structural uncertainties and the Brownian noise (Wiener process). The key features of the proposed method are to apply singular value decomposition (SVD) to all structural uncertainties, to introduce adjustable parameters for control design along with the SMC method, and new Lyapunov-type functional. Then, a less-conservative condition for robust stability and a new robust controller for the general uncertain stochastic systems are derived via linear matrix inequality (LMI) forms. The system states are able to reach the SMC switching surface as guaranteed in probability 1 by the proposed control rule. Furthermore, the novel Lyapunov-type functional for the uncertain stochastic systems is used to design a new robust control for the general case where the derivative of time-varying delay can be any bounded value (e.g., greater than one). It is theoretically proved that the conservatism of the proposed method is less than the previous methods.
All theoretical proofs are presented in the dissertation. The simulations validate the correctness of the theoretical results and have better performance than the existing results
- …