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Learning-Based MPC for Fuel Efficient Control of Autonomous Vehicles with Discrete Gear Selection
Samuel Mallick, Gianpietro Battocletti, Qizhang Dong +2
Co-optimization of both vehicle speed and gear position via model predictive control (MPC) has been shown to offer benefits for fuel-efficient autonomous driving. However, optimizi…
Approximate Dynamic Programming for Constrained Piecewise Affine Systems with Stability and Safety Guarantees
Kanghui He, Shengling Shi, Ton van den Boom +1
Infinite-horizon optimal control of constrained piecewise affine (PWA) systems has been approximately addressed by hybrid model predictive control (MPC), which, however, has comput…
State-action control barrier functions: Imposing safety on learning-based control with low online computational costs
Kanghui He, Shengling Shi, Ton van den Boom +1
Learning-based control with safety guarantees usually requires real-time safety certification and modifications of possibly unsafe learning-based policies. The control barrier func…
Proactive Emergency Collision Avoidance for Automated Driving in Highway Scenarios
Leila Gharavi, Azita Dabiri, Jelske Verkuijlen +2
Uncertainty in the behavior of other traffic participants is a crucial factor in collision avoidance for automated driving; here, stochastic metrics could avoid overly conservative…
A Comparison Benchmark for Distributed Hybrid MPC Control Methods: Distributed Vehicle Platooning
Samuel Mallick, Azita Dabiri, Bart De Schutter
Distributed model predictive control (MPC) is currently being investigated as a solution to the important control challenge presented by networks of hybrid dynamical systems. Howev…
Sensitivity Analysis for Piecewise-Affine Approximations of Nonlinear Programs with Polytopic Constraints
Leila Gharavi, Changrui Liu, Bart De Schutter +1
Nonlinear Programs (NLPs) are prevalent in optimization-based control of nonlinear systems. Solving general NLPs is computationally expensive, necessitating the development of fast…