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Showing 1 to 7 of 7 for “"Hamilton-Jacobi-Bellman (HJB) equation"”.

  1. A new method for suboptimal control of a class of nonlinear systems

    … by finding an approximate solution to the Hamilton-Jacobi-Bellman (HJB) equation."--Abstract, page iii.

    must-thes Repository record for A new method for suboptimal control of a class of nonlinear systems (opens in a new tab)

  2. Finite time suboptimal control design of nonlinear systems with θ-D technique and implementation to aerospace applications

    … that, the approximated solutions to intractable Hamilton-Jacobi-Bellman (HJB) equation were acquired by putting vanishing perturbation terms into the performance index. By tuning the parameters in perturbation terms, semi-global stability and sub-optimalilty was guaranteed. By taking the …

    must-thes Repository record for Finite time suboptimal control design of nonlinear systems with θ-D technique and implementation to aerospace applications (opens in a new tab)

  3. Essays in financial economics

    … the corresponding nonlinear partial differential equations (PDEs) can be recast as a sequence of supervised learning problems. Furthermore, I propose a setting to test and evaluate solution methods. In the context of a Neoclassical Growth Model, given any value function, the productivity function …

    mit Repository record for Essays in financial economics (opens in a new tab)

  4. Event-triggered near optimal adaptive control of interconnected systems

    … learning (RL) approach is proposed to solve the Hamilton-Jacobi-Bellman (HJB) equation by using neural networks (NNs) for generating distributed optimal control of nonlinear interconnected systems using state and output feedback. To relax the state vector measurements, distributed observers are …

    must-thes Repository record for Event-triggered near optimal adaptive control of interconnected systems (opens in a new tab)

  5. Dynamic Neural Network-based Adaptive Inverse Optimal Control Design

    … function (CLF). The CLF must satisfy the partial Hamilton Jacobi-Bellman (HJB) equation to solve the cost function in order to prove the optimality. In other words, the control design is derived from the CLF and inversely achieves optimality when the given cost function variables are determined …

    siu-theses Repository record for Dynamic Neural Network-based Adaptive Inverse Optimal Control Design (opens in a new tab)

  6. Metrics, fundamental trade-offs and control policies for delay-sensitive applications in volatile environments

    … with a probabilistic constraint. We present the Hamilton-Jacobi-Bellman (HJB) equation for this problem by expanding the state space, and exploit it as a verification method for optimality of the proposed control policy. We use the tools and techniques developed for media streaming applications …

    mit Repository record for Metrics, fundamental trade-offs and control policies for delay-sensitive applications in volatile environments (opens in a new tab)

  7. Noncooperative static and dynamic games: addressing shared constraints and phase transitions

    … controlled N-dimensional stochastic differential equation model, coupled only through a cost function. The states are interpreted as phase angles for a collection of non-homogeneous oscillators, and in this way the model may be regarded as an extension of the classical coupled oscillator model of …

    uiuc Repository record for Noncooperative static and dynamic games: addressing shared constraints and phase transitions (opens in a new tab)