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Predictive Control for Linear and Hybrid Systems
TLDR
Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.
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Constrained Optimal Control of Linear and Hybrid Systems
  • F. Borrelli
  • Computer Science, Mathematics
    IEEE Transactions on Automatic Control
  • 5 August 2003
TLDR
Constrained Optimal Control for Hybrid Systems and Ball and Plate Control and Reducing On-line Complexity.
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Model predictive control based on linear programming - the explicit solution
TLDR
The availability of the explicit structure of the MPC controller provides an insight into the type of control action in different regions of the state space, and highlights possible conditions of degeneracies of the LP, such as multiple optima.
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Predictive Active Steering Control for Autonomous Vehicle Systems
TLDR
The effectiveness of the proposed MPC formulation is demonstrated by simulation and experimental tests up to 21 m/s on icy roads, and two approaches with different computational complexities are presented.
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Distributed LQR Design for Identical Dynamically Decoupled Systems
TLDR
The design procedure proposed in this paper illustrates how stability of the large-scale system is related to the robustness of local controllers and the spectrum of a matrix representing the desired sparsity pattern of the distributed controller design problem.
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Min-max control of constrained uncertain discrete-time linear systems
TLDR
It is shown that the finite-horizon robust optimal control law is a continuous piecewise affine function of the state vector and can be calculated by solving a sequence of multiparametric linear programs.
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Decentralized receding horizon control for large scale dynamically decoupled systems
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Geometric Algorithm for Multiparametric Linear Programming
TLDR
A novel algorithm for solving multiparametric linear programming problems that follows a geometric approach based on the direct exploration of the parameter space and has computational advantages, namely the simplicity of its implementation in a recursive form and an efficient handling of primal and dual degeneracy.
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Distributed Model Predictive Control for Heterogeneous Vehicle Platoons Under Unidirectional Topologies
TLDR
It is proved that asymptotic stability of such a DMPC can be achieved through an explicit sufficient condition on the weights of the cost functions, by using the sum of local cost functions as a Lyapunov candidate.
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Kinematic and dynamic vehicle models for autonomous driving control design
TLDR
Experimental results show the effectiveness of the proposed approach at various speeds on windy roads, and it is shown that it is less computationally expensive than existing methods which use vehicle tire models.
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