Fully Parameterized Tube MPC

Raković, Sas̆a V.; Kouvaritakis, B.; Cannon, Mark; Panos, Christos; Findeisen, Rolf

doi:10.3182/20110828-6-it-1002.03110

Cited by 29 publications

(23 citation statements)

References 6 publications

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“…As mentioned above, a local feedback controller is needed to track the reference trajectory generated by the MPC. The idea of centralized tube MPC was discussed in [43], [44], and was extended to distributed tube MPC for multiple subsystems without coupling in the dynamics [45]. There exist, however, strong coupling between nodes in the models of the grid dynamics that we consider.…”

Section: B Contingency Tube Mpc With Cbfmentioning

confidence: 99%

Safety-Critical Control Synthesis for Network Systems With Control Barrier Functions and Assume-Guarantee Contracts

Chen

Anderson

Kalsi

et al. 2021

IEEE Trans. Control Netw. Syst.

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This paper presents a contract based framework for safety-critical control synthesis for network systems. To handle the large state dimension of such systems, an assume-guarantee contract is used to break the large synthesis problem into smaller subproblems. Parameterized signal temporal logic (pSTL) is used to formally describe the behaviors of the subsystems, which we use as the template for the contract. We show that robust control invariant sets (RCIs) for the subsystems can be composed to form a robust control invariant set for the whole network system under a valid assume-guarantee contract. An epigraph algorithm is proposed to solve for a contract that is valid,-an approach that has linear complexity for a sparse network, which leads to a robust control invariant set for the whole network. Implemented with control barrier function (CBF), the state of each subsystem is guaranteed to stay within the safe set. Furthermore, we propose a contingency tube Model Predictive Control (MPC) approach based on the robust control invariant set, which is capable of handling severe contingencies, including topology changes of the network. A power grid example is used to demonstrate the proposed method. The simulation result includes both set point control and contingency recovery, and the safety constraint is always satisfied.

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Section: B Contingency Tube Mpc With Cbfmentioning

confidence: 99%

Safety-Critical Control Synthesis for Network Systems With Control Barrier Functions and Assume-Guarantee Contracts

Chen

Anderson

Kalsi

et al. 2021

IEEE Trans. Control Netw. Syst.

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show abstract

“…There are different approaches in the literature which deal with the reference trajectory tracking problem for dynamical systems affected by disturbances. A classical method is based on the tube MPC approach (for details, the reader is referred to (Rakovic et al, 2011;Mayne et al, 2011)) where a nominal trajectory is controlled and the real trajectory is kept into a tube around the nominal one through a suitable control action.…”

Section: Trajectory Tracking Control Problemmentioning

confidence: 99%

Receding horizon flight control for trajectory tracking of autonomous aerial vehicles

Prodan

Olaru

Bencatel

et al. 2013

Control Engineering Practice

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International audienceThis paper addresses the implementation of a predictive control strategy for Unmanned Air Vehicles in the presence of bounded disturbances. The goal is to prove the feasibility of such a real-time optimization-based control design and to demonstrate its tracking capabilities for the nonlinear dynamics with respect to a reference trajectory which is pre-specified via differential flatness. In order to benefit from the computational advantages of the linear predictive control formulations, an off-line linearization strategy of the nonlinear model of the vehicle along the flat trajectory is employed. The proposed method exhibits effective performance validated through software-in-the-loop simulations and real flight tests on different Unmanned Aerial Vehicles (UAVs)

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“…There are different approaches in the literature which deal with the reference trajectory tracking problem for dynamical systems affected by disturbances. A classical method is based on the tube MPC approach (for details, the reader is referred to [Mayne et al, 2006], [Rakovic et al, 2011]), where a nominal trajectory is controlled and the real trajectory is kept into a tube around the nominal one through a suitable control action.…”

Section: Trajectory Tracking Problemmentioning

confidence: 99%

“…For reducing the computation effort we use the "nominal" behavior of the vehicle and consider safety region (the reader can refer to our previous work [Prodan et al, 2011]) around it to compensate for the effects of the disturbances affecting the "real" system. Furthermore, these regions can be defined within the theory of invariant sets [Rakovic et al, 2011] in order to avoid recomputations during the real-time functioning [Mayne et al, 2006].…”

Section: Introductionmentioning

confidence: 99%

Predictive Control for Autonomous Aerial Vehicles Trajectory Tracking

Prodan

Bencatel

Olaru

et al. 2012

IFAC Proceedings Volumes

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This paper addresses a predictive control strategy for Unmanned Air Vehicles in the presence of bounded disturbances. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified using the differential flatness formalism. Furthermore, an off-line linearization strategy of the nonlinear model of the vehicle along the flat trajectory is proposed. Since the reference trajectory is available beforehand, an optimization problem which minimizes the tracking error for the vehicle is formulated in a predictive control framework. The proposed method exhibits effective performance validated through software-in-the-loop simulations for the control of Unmanned Aerial Vehicles (UAVs).

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Fully Parameterized Tube MPC

Cited by 29 publications

References 6 publications

Safety-Critical Control Synthesis for Network Systems With Control Barrier Functions and Assume-Guarantee Contracts

Safety-Critical Control Synthesis for Network Systems With Control Barrier Functions and Assume-Guarantee Contracts

Receding horizon flight control for trajectory tracking of autonomous aerial vehicles

Predictive Control for Autonomous Aerial Vehicles Trajectory Tracking

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