To guarantee stability of a model predictive control scheme it is essential to suitably calculate the terminal region and the terminal penalty term. In this paper we propose an approach to overcome this problem for th...
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ISBN:
(纸本)9783902661555
To guarantee stability of a model predictive control scheme it is essential to suitably calculate the terminal region and the terminal penalty term. In this paper we propose an approach to overcome this problem for the class of periodically time-varying systems. We consider both systems with periodic linear dynamics as well as systems with periodic nonlinear dynamics where the nonlinearities can be approximated with polytopic linear differential inclusions. In both cases exploiting the periodicity of the system dynamics leads to linear matrix inequality (LMI) conditions which can be used to calculate the terminal region and the terminal penalty term. The LMI conditions are shown to be less conservative than existing approaches applicable to the considered system class.
In this paper, a receding horizon control scheme able to stabilize linear periodic time-varying systems, in the sense of asymptotic convergence, is proposed. The presented approach guarantees that input constraints ar...
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This paper presents a computationally attractive nonlinear model predictive control approach for the class of continuous time Lure systems. The control law is obtained via the repeated solution of an efficient to solv...
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Nonlinear systems can be poorly or non-observable along specific state and output trajectories or in certain regions of the state space. Operating the system along such trajectories or in such regions can lead to poor...
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In ambition to minimize potential interferences between yaw stabilization and rollover prevention of an automotive vehicle, this work presents a new approach to integrate both objectives. It introduces rollover preven...
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In order to study the structural properties of electrical network over F(z), it is necessary to analyze the coefficient matrix A of the state equations .In paper [8], author has proved that the characteristic roots of...
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The paper presents a moving horizon 2 control approach for the class of linear parameter-varying systems. By solving online a convex optimization problem subject to linear matrix inequality constraints the 2 gain from...
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ISBN:
(纸本)9783902661555
The paper presents a moving horizon 2 control approach for the class of linear parameter-varying systems. By solving online a convex optimization problem subject to linear matrix inequality constraints the 2 gain from the energy bounded external disturbance to the performance output is minimized at each sampling instant. The approach guarantees satisfaction of state and input constraints and it is shown that the online recalculation of the control law improves disturbance attenuation significantly when compared to a static control law.
Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding searc...
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ISBN:
(纸本)9783902661593
Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding search spaces. This contribution proposes an approach to computing hybrid optimal control trajectories based on an iterative model-abstraction and refinement scheme. The hybrid automaton is mapped to an abstract representation which is enriched by cost information gained from graph. Candidate solutions are computed on the abstract level and are mapped back to the level of the hybrid model, where they are validated. A refinement step guides the search for (sub-) optimal hybrid control trajectories. The proposed approach is implemented for the optimization of the start-up procedure for a chemical reactor.
Analysis and safety considerations of chemical and biological processes frequently require an outer approximation of the set of all feasible steady-states. Nonlinearities, uncertain parameters, and discrete variables ...
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ISBN:
(纸本)9783902661548
Analysis and safety considerations of chemical and biological processes frequently require an outer approximation of the set of all feasible steady-states. Nonlinearities, uncertain parameters, and discrete variables complicate the calculation of guaranteed outer bounds. In this paper, the problem of outer-approximating the region of feasible steady-states, for processes described by uncertain nonlinear differential algebraic equations including discrete variables and discrete changes in the dynamics, is adressed. The calculation of the outer bounding sets is based on a relaxed version of the corresponding feasibility problem. It uses the Lagrange dual problem to obtain certificates for regions in state space not containing steady-states. These infeasibility certificates can be computed efficiently by solving a semidefinite program, rendering the calculation of the outer bounding set computationally feasible. The derived method guarantees globally valid outer bounds for the steady-states of nonlinear processes described by differential equations. It allows to consider discrete variables, as well as switching system dynamics. The method is exemplified by the analysis of a simple chemical reactor showing parametric uncertainties and large variability due to the appearance of bifurcations characterising the ignition and extinction of a reaction.
Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems wit...
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Dynamic programming provides a method to solve hybrid optimal control problems. This contribution extends existing numerical methods originally developed for purely continuous systems, to a class of hybrid systems with autonomous as well as controlled switching behavior. The hybrid dynamics is approximated by a locally consistent discrete Markov decision process. The original optimal control problem is then reformulated for the Markov decision process and solved by standard dynamic programming methods. The convergence of the discrete approximation to the original problem is ensured. The viability of the numerical scheme is illustrated by a two gear transmission system used previously in literature.
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