Abstract:
The Report describes the Linear Quadratic Regulator(LQR) and the study of the linear
systems on different types of systems i.e single agent and multi-agent systems.Different
approaches are available for creating an optimal controller for the Linear system where
the dynamics of the systems are unknown. One such approach is approximate/adaptive
dynamic programming approach(ADP). The algorithm have been implemented for both
single and multi-agent system. The algorithm have two level of working one is off-policy
data storage and rank checking and the second level is on-policy online reinforcement
iterative approach.This paper follows a similar techniques as defined in [1] using dual
layer filtering to achieve the optimal control values. In the first layer we are eliminating
the state derivative and in the second layer we are iterating under the initial excitation
technique to get the optimal values for our dynamical system. The Initial Excitation described in this paper method solve the problem of data storage in the Adaptive Optimal
Control(AOC) method and uses a two-level filter approach. The algorithm is designed for
single agent system and it was implemented on multi-agent system.
