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State-action control barrier functions: Imposing safety on learning-based control with low online computational costs
Learning-based control with safety guarantees usually requires real-time safety certification and modifications of possibly unsafe learning-based policies.
Approximate Dynamic Programming for Constrained Piecewise Affine Systems with Stability and Safety Guarantees
Infinite-horizon optimal control of constrained piecewise affine (PWA) systems has been approximately addressed by hybrid model predictive control (MPC), which, however, has computational limitations, both in offline design and online implementation.
Approximate Dynamic Programming for Constrained Linear Systems: A Piecewise Quadratic Approximation Approach
A novel convex and piecewise quadratic neural network with a local-global architecture is proposed to provide an accurate approximation of the value function, which is used as the cost-to-go function in the online dynamic programming problem.
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