Towards combining nonlinear and predictive control of diesel engines

Huang, Mike; Nakada, Hayato; Polavarapu, Srinivas; Choroszucha, Richard; Butts, Ken; Kolmanovsky, Ilya

doi:10.1109/acc.2013.6580266

Cited by 20 publications

(8 citation statements)

References 9 publications

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“…Diesel engine airpath control: This benchmark contains a simplified version of the system presented in [17]. It is a piecewise affine representation of a diesel engine model and a model-predictive controller regulating the intake manifold pressure in the engine.…”

Section: Case Studiesmentioning

confidence: 99%

Multiple shooting, CEGAR-based falsification for hybrid systems

Zutshi

Deshmukh

Sankaranarayanan

et al. 2014

Proceedings of the 14th International Conference on Embedded Software

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In this paper, we present an approach for finding violations of safety properties of hybrid systems. Existing approaches search for complete system trajectories that begin from an initial state and reach some unsafe state. We present an approach that searches over segmented trajectories, consisting of a sequence of segments starting from any system state. Adjacent segments may have gaps, which our approach then seeks to narrow iteratively. We show that segmented trajectories are actually paths in the abstract state graph obtained by tiling the state space with cells. Instead of creating the prohibitively large abstract state graph explicitly, our approach implicitly performs a randomized search on it using a scatter-andsimulate technique. This involves repeated simulations, graph search to find likeliest abstract counterexamples, and iterative refinement of the abstract state graph. Finally, we demonstrate our technique on a number of case studies ranging from academic examples to models of industrial-scale control systems.

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Section: Case Studiesmentioning

confidence: 99%

Multiple shooting, CEGAR-based falsification for hybrid systems

Zutshi

Deshmukh

Sankaranarayanan

et al. 2014

Proceedings of the 14th International Conference on Embedded Software

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Section: Introductionmentioning

confidence: 99%

“…Recently, MPC has been applied to an 8th order DAP model in [5] and [6]. To reduce computational complexity, an explicit model predictive controller (eMPC) using open-loop model order reduction [5] was demonstrated. The follow-up work [6] applied an explicit rate-based MPC controller [7] using a single reduced order linearization over the entire fuel/engine speed operating space.…”

Section: Introductionmentioning

confidence: 99%

Closed-loop model order reduction and MPC for diesel engine airpath control

Choroszucha

Sun

Butts³

2015

2015 American Control Conference (ACC)

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This paper explores MPC for an 8th order air path dynamic model for an automotive diesel engine system. The relatively high order of the system makes the MPC realtime implementation on a practical engine control unit (ECU) infeasible, thereby motivating the model order reduction effort. For the MPC problem with terminal state penalty, Riccatibalanced truncation is used to find a reduced order model for the design of MPC. The presence of a direct feedthrough term from the input to the output in the model requires special treatment and is addressed. We present the analysis of the MPC designs for different reduced order models, compare the reduced order models through open-loop and closed-loop reduction methods, and demonstrate the performance of the resulting linear MPC on a proprietary nonlinear diesel model.

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“…This system has been the subject of recent experimental work in the automotive industry and has appeared ṗ = c1 recently in the literature [11]. There has been interest in adopting MPC in the automotive industry, but several hurdles remain, such as the ability to prove safety properties of the closed-loop system.…”

Section: Example 6: Mpc For Engine Control Systemmentioning

confidence: 99%

“…Given a Lyapunov template v(x) = z T Pz, the set of feasible solutions that satisfy (2) and (3) is convex in the decision variable P. Adding constraints (9) to (11) bounds the feasible set with linear constraints. Thus the feasible set lies on the interior of the linear constraints.…”

Section: Constructing Candidatesmentioning

confidence: 99%

Simulation-guided lyapunov analysis for hybrid dynamical systems

Kapinski

Deshmukh

Sankaranarayanan

et al. 2014

Proceedings of the 17th International Conference on Hybrid Systems: Computation and Control

122

126

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Lyapunov functions are used to prove stability and to obtain performance bounds on system behaviors for nonlinear and hybrid dynamical systems, but discovering Lyapunov functions is a difficult task in general. We present a technique for discovering Lyapunov functions and barrier certificates for nonlinear and hybrid dynamical systems using a searchbased approach. Our approach uses concrete executions, such as those obtained through simulation, to formulate a series of linear programming (LP) optimization problems; the solution to each LP creates a candidate Lyapunov function. Intermediate candidates are iteratively improved using a global optimizer guided by the Lie derivative of the candidate Lyapunov function. The analysis is refined using counterexamples from a Satisfiability Modulo Theories (SMT) solver. When no counterexamples are found, the soundness of the analysis is verified using an arithmetic solver. The technique can be applied to a broad class of nonlinear dynamical systems, including hybrid systems and systems with polynomial and even transcendental dynamics. We present several examples illustrating the efficacy of the technique, including two automotive powertrain control examples.

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Towards combining nonlinear and predictive control of diesel engines

Cited by 20 publications

References 9 publications

Multiple shooting, CEGAR-based falsification for hybrid systems

Multiple shooting, CEGAR-based falsification for hybrid systems

Closed-loop model order reduction and MPC for diesel engine airpath control

Simulation-guided lyapunov analysis for hybrid dynamical systems

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