Embedding Constrained Model Predictive Control in a Continuous-Time Dynamic Feedback

Nicotra, Marco M.; Liao‐McPherson, Dominic; Kolmanovsky, Ilya

doi:10.1109/tac.2018.2867359

Cited by 39 publications

(19 citation statements)

References 55 publications

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“…Although employing warm-starting [36] can improve convergence of the virtual dynamical system in dynamically embedded MPC, guaranteeing recursive feasibility (i.e., remaining feasible indefinitely) with this scheme is challenging, as a sudden change in the reference signal can drastically change the problem specifics, e.g., the terminal set may not be reachable anymore within the given prediction horizon. To address this issue, in [37], the dynamically embedded MPC is augmented with an Explicit Reference Governor (ERG) [38,39,40]; however, this may lead to conservative (slow) response due to conservatism of ERG.…”

Section: Prior Work On Optimization-based Constrained Control Ofmentioning

confidence: 99%

“…Our approach to CG implementation is inspired by [43,44] in exploiting barrier functions and the primal-dual continuoustime flow algorithm, but addresses a different problem. Our proofs of convergence are inspired by Lyapunov-based approaches in [35,37,45], but once again explored for a different problem.…”

Section: Contributionmentioning

confidence: 99%

“…Note that once task τ N is terminated, there will be no time to implement the mechanism (37) and compute corresponding control input. To address this issue, during the run-time of the virtual system (step 3), we continuously implement the mechanism (step 4) and update and store in memory the control input (step 5) without applying it to the system.…”

Section: Rotecmentioning

confidence: 99%

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ROTEC: Robust to Early Termination Command Governor for Systems with Limited Computing Capacity

Hosseinzadeh¹,

Sinopoli²,

Kolmanovsky³

et al. 2022

Preprint

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A Command Governor (CG) is an optimization-based add-on scheme to a nominal closed-loop system. It is used to enforce state and control constraints by modifying reference commands. This paper considers the implementation of a CG on embedded processors that have limited computing resources and must execute multiple control and diagnostics functions; consequently, the time available for CG computations is limited and may vary over time. To address this issue, a robust to early termination command governor is developed which embeds the solution of a CG problem into the internal states of a virtual continuous-time dynamical system which runs in parallel to the process. This virtual system is built so that its trajectory converges to the optimal solution (with a tunable convergence rate), and provides a sub-optimal but feasible solution whenever its evolution is terminated. This allows the designer to implement a CG strategy with a small sampling period (and consequently with a minimum degradation in its performance), while maintaining its constraint-handling capabilities. Simulations are carried out to assess the effectiveness of the developed scheme in satisfying performance requirements and real-time schedulability conditions for a practical vehicle rollover example.

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Section: Prior Work On Optimization-based Constrained Control Ofmentioning

confidence: 99%

Section: Contributionmentioning

confidence: 99%

Section: Rotecmentioning

confidence: 99%

See 1 more Smart Citation

ROTEC: Robust to Early Termination Command Governor for Systems with Limited Computing Capacity

Hosseinzadeh¹,

Sinopoli²,

Kolmanovsky³

et al. 2022

Preprint

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show abstract

“…This optimization problem is convex and can be solved for a small number of permissible strategies using standard Matlab Optimization Toolbox software. In practice, however, it may be necessary to use a greater number of acceptable players strategies, then the solution of such a real-time game control task can be achieved using parallel continuous-time solvers, as presented by Hosseinzadeh et al [29] for multi-agent smart systems and Nicotra et al [30] in relation to the problem of optimal control, which can be embedded in the internal states of a dynamic control law running in parallel to the system.…”

Section: Game Control Algorithmmentioning

confidence: 99%

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Lisowski

2021

Electronics

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This paper describes and illustrates the optimization of a safe mobile robot control process in collision situations using the model of a multistep matrix game of many participants in the form of a dual linear programming problem. The synthesis of non-cooperative and cooperative game control software was performed in Matlab/Simulink software to determine the safe path of the robot when passing a greater number of other robots and obstacles. The operation of the game motion control algorithm of a mobile robot is illustrated by computer simulations made in the Matlab/Simulink program of two real previously recorded navigation situations while passing dozens of other autonomous mobile robots.

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“…in [38]. These methods use some combination of shifting terminal control updates and first order optimization methods.…”

Section: Introductionmentioning

confidence: 99%

Time-distributed optimization for real-time model predictive control: Stability, robustness, and constraint satisfaction

2020

Self Cite

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Time distributed optimization is an implementation strategy that can significantly reduce the computational burden of model predictive control by exploiting its robustness to incomplete optimization. When using this strategy, optimization iterations are distributed over time by maintaining a running solution estimate for the optimal control problem and updating it at each sampling instant. The resulting controller can be viewed as a dynamic compensator which is placed in closedloop with the plant. This paper presents a general systems theoretic analysis framework for time distributed optimization. The coupled plant-optimizer system is analyzed using input-to-state stability concepts and sufficient conditions for stability and constraint satisfaction are derived. When applied to time distributed sequential quadratic programming, the framework significantly extends the existing theoretical analysis for the real-time iteration scheme. Numerical simulations are presented that demonstrate the effectiveness of the scheme.

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Embedding Constrained Model Predictive Control in a Continuous-Time Dynamic Feedback

Cited by 39 publications

References 55 publications

ROTEC: Robust to Early Termination Command Governor for Systems with Limited Computing Capacity

ROTEC: Robust to Early Termination Command Governor for Systems with Limited Computing Capacity

Synthesis of a Path-Planning Algorithm for Autonomous Robots Moving in a Game Environment during Collision Avoidance

Time-distributed optimization for real-time model predictive control: Stability, robustness, and constraint satisfaction

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