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CT系統的结构与组成设计方案
Online actor–critic algorithm to solve the continuous-time infinite horizon optimal control problem? In this paper we discuss an online algorithm based on policy iteration for learning the continuous-time (CT) optimal control solution with infinite horizon cost for nonlinear systems with known dynamics. That is, the algorithm learns online in real-time the solution to the optimal control design HJ equation. This method finds in real-time suitable approximations of both the optimal cost and the optimal control policy, while also guaranteeing closed-loop stability. We present an online adaptive algorithm implemented as an actor/critic structure which involves simultaneous continuous-time adaptation of both actor and critic neural networks. We call this ‘synchronous’ policy iteration. A persistence of excitation condition is shown to guarantee convergence of the critic to the actual optimal value function. Novel tuning algorithms are given for both critic and actor networks, with extra nonstandard terms in the actor tuning law being required to guarantee closed-loop dynamical stability. The convergence to the optimal controller is proven, and the stability of the system is also guaranteed. Simulation examples show the effectiveness of the new algorithm. Inter- and intraobserver variability in the postoperative evaluation of transpedicular stabilization: computed tomography versus magnetic resonance imaging? Computed tomography (CT) represents the state of the art for the postoperative verification of the implant position after transpedicular stabilizations. Magnetic resonance imaging (MRI) has not challenged the CT, yet, because of susceptibility artifacts but would be favorable as a diagnostic tool for its excellent soft-tissue qualities. Purpose A study that analyzed if an artifact-reduced MRI could overcome this problem and provide sufficient data for the postoperative assessment was conducted. Study design The study design was a radiologic comparison of CT
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