iterative optimal control algorithm
Parameter Optimal Iterative Learning Control with Application to a Robot Arm
... parameter optimal iterative learning control to control the robot arm is ...the iterative learning control with the optimization is an alternative way to successfully achieve a ...
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A Gauss Newton Approach for Nonlinear Optimal Control Problem with Model Reality Differences
... the control trajectory is updated itera- tively by using the Gauss-Newton ...the optimal control law is constructed from the model-based optimal control problem, which is not adding the ...
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Fast Norm Optimal Iterative Learning Control for Industrial Applications
... the algorithm is extremely well justified by the significant improvements in tracking error reduction and convergence rate, when compared to simpler algorithms which require no form of plant ...the ...
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A Probabilistic Algorithm for Optimal Control Problem
... The idea of dynamic programing was first introduced in the middle of the last century [1] and later developed into the Bellman principle of optimality [2, 3]. Methods based on this principle however, are often ...
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Discrete Time Nonlinear Stochastic Optimal Control Problem Based on Stochastic Approximation Approach
... linear optimal control model with model-reality dif- ferences in solving the nonlinear optimal control problem, especially for dis- crete-time nonlinear stochastic optimal ...
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A gradient algorithm for optimal control problems with model reality differences
... of optimal control problem is ...model-based optimal control problem is discussed, where the adjusted parameters are added into the model ...modified optimal control problem, ...
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Analysis and Causal Formulation Proof of an Optimal Iterative Learning Algorithm
... a control input) and observing what was the end result of this control input ...new control input) in order to get an improved performance during the next ...correct control input, and b) ...
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Evaluation of Minimum Makespan using Modified Evolutionary Algorithm
... genetic algorithm repeats evaluation, selection, crossover and mutation after initialization until the stopping condition is ...Genetic algorithm is naturally parallel, exhibits implicit parallelism [11]; ...
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Output regulation for discrete time nonlinear stochastic optimal control problems with model reality differences
... integrated optimal control algorithm for solving discrete-time nonlinear stochastic optimal control problems has been proposed, see for examples [3], [9], [10] and ...developed ...
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Limit sets and switching strategies in parameter-optimal iterative learning control
... In what follows, it will be seen that the use of switching algorithms based on causal filters and the choice of a sequence of stable filter poles uniformly distributed in ( − 1, 1) has the potential to greatly improve ...
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Iterative Solution of Mesh Constrained Optimal Control Problems with Two Level Mesh Approximations of Parabolic State Equation
... the iterative methods for parabolic optimal control problems include the solution of the parabolic equation and corresponding ad- joint parabolic equation at each iteration and this is the most time ...
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An Iterative Technique for Solving Nonlinear Optimal Control Problems Using Legendre Scaling Function
... For the last three decades, orthogonal functions and polynomials series [1-4] have been used in approximation methods to obtain the optimal solution of linear time invariant, time varying, and nonlinear systems. ...
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SPOT: Sliced Partial Optimal Transport
... Optimal transport is a popular mathematical framework for manip- ulating positive measures, and in particular, in most cases studied so far, probability measures. It has become widespread in computer graphics ...
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Simulation Studies on Image Reconstruction Algorithm for Portable Electrical Capacitance Tomography
... enough for phantom (b) and (c). GVSPM algorithms show tolerable value for correlation coefficient which is quite close to Landweber while the moderate value is gained from LBP algorithms. In order to compare the speed of ...
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Stability Analysis of a Second-Order Proportionally-Fair Rate Allocation Algorithm
... Although, the conditions have been simplied by this assumption that all network users have the same propagation delays, in the general case of dierent propagation delays, the algorithm has been simulated and the ...
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MMAR 2017 Lecture Schedule - Compact Form Monday, 15:10-16:10. Monday, 16:30-17:50
... Adaptive Optimal Control Algorithm for Vibrational Systems Under Nonlinear. Friction Wasilewski, Pisarski[r] ...
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The Newton-like properties of the updating mechanism of a model-reality differences algorithm
... (DISOPE) algorithm is an algorithm for solving nonlinear optimal con- trol problems and is of the gradient descent ...the algorithm and hence in determining its rate of ...
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H Singular Value of a Positive Tensor
... an iterative algorithm to calculate the largest H-singular value of a positive tensor based on Theorem 2 and Theorem ...This algorithm is a modified version of the one given in [11] [13], and we will ...
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Optimal Design of Non-equilibrium Experiments for Genetic Network Interrogation
... an optimal de- sign algorithm that calculates optimal observation times in conjunction with optimal experimental perturbations in order to maximize the amount of information gained from ...
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Quantitative Determination Of Optimal Fiscal And Monetary Policies: A Stochastic Optimal Control Analysis For Iran
... of optimal control theory has been widely developed in economic ...Stochastic optimal control theory is a powerful tool for solving these problems and for this purpose, some stochastic ...
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