1,316 research outputs found
Al'brekht's Method in Infinite Dimensions
In 1961 E. G. Albrekht presented a method for the optimal stabilization of smooth, nonlinear, finite dimensional, continuous time control systems. This method has been extended to similar systems in discrete time and to some stochastic systems in continuous and discrete time. In this paper we extend Albrekht's method to the optimal stabilization of some smooth, nonlinear, infinite dimensional, continuous time control systems whose nonlinearities are described by Fredholm integral operators
Random Finite Set Theory and Optimal Control of Large Collaborative Swarms
Controlling large swarms of robotic agents has many challenges including, but
not limited to, computational complexity due to the number of agents,
uncertainty in the functionality of each agent in the swarm, and uncertainty in
the swarm's configuration. This work generalizes the swarm state using Random
Finite Set (RFS) theory and solves the control problem using Model Predictive
Control (MPC) to overcome the aforementioned challenges. Computationally
efficient solutions are obtained via the Iterative Linear Quadratic Regulator
(ILQR). Information divergence is used to define the distance between the swarm
RFS and the desired swarm configuration. Then, a stochastic optimal control
problem is formulated using a modified L2^2 distance. Simulation results using
MPC and ILQR show that swarm intensities converge to a target destination, and
the RFS control formulation can vary in the number of target destinations. ILQR
also provides a more computationally efficient solution to the RFS swarm
problem when compared to the MPC solution. Lastly, the RFS control solution is
applied to a spacecraft relative motion problem showing the viability for this
real-world scenario.Comment: arXiv admin note: text overlap with arXiv:1801.0731
Model order reduction approaches for infinite horizon optimal control problems via the HJB equation
We investigate feedback control for infinite horizon optimal control problems
for partial differential equations. The method is based on the coupling between
Hamilton-Jacobi-Bellman (HJB) equations and model reduction techniques. It is
well-known that HJB equations suffer the so called curse of dimensionality and,
therefore, a reduction of the dimension of the system is mandatory. In this
report we focus on the infinite horizon optimal control problem with quadratic
cost functionals. We compare several model reduction methods such as Proper
Orthogonal Decomposition, Balanced Truncation and a new algebraic Riccati
equation based approach. Finally, we present numerical examples and discuss
several features of the different methods analyzing advantages and
disadvantages of the reduction methods
H2 Optimal Coordination of Homogeneous Agents Subject to Limited Information Exchange
Controllers with a diagonal-plus-low-rank structure constitute a scalable
class of controllers for multi-agent systems. Previous research has shown that
diagonal-plus-low-rank control laws appear as the optimal solution to a class
of multi-agent H2 coordination problems, which arise in the control of wind
farms. In this paper we show that this result extends to the case where the
information exchange between agents is subject to limitations. We also show
that the computational effort required to obtain the optimal controller is
independent of the number of agents and provide analytical expressions that
quantify the usefulness of information exchange
Optimal discrete-time LQR problems for parabolic systems with unbounded input: Approximation and convergence
An abstract approximation and convergence theory for the closed-loop solution of discrete-time linear-quadratic regulator problems for parabolic systems with unbounded input is developed. Under relatively mild stabilizability and detectability assumptions, functional analytic, operator techniques are used to demonstrate the norm convergence of Galerkin-based approximations to the optimal feedback control gains. The application of the general theory to a class of abstract boundary control systems is considered. Two examples, one involving the Neumann boundary control of a one-dimensional heat equation, and the other, the vibration control of a cantilevered viscoelastic beam via shear input at the free end, are discussed
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