A minimum-time optimal recharging control strategy for high pressure gas storage tank systems is described in this work. The goal of the nonlinear model-based controller is to refill the tank in minimum time with a tw...
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ISBN:
(纸本)9783540726982
A minimum-time optimal recharging control strategy for high pressure gas storage tank systems is described in this work. The goal of the nonlinear model-based controller is to refill the tank in minimum time with a two-component gas mixture of specified composition subject to hard constraints on the component flow rates, tank temperature, and tank pressure. The nonlinearity in this system arises from the nonideal behavior of the gas at high pressure. The singular minimum-time optimal control law can not be reliably implemented in the target application due to a lack of sensors. Minimum-time optimal control is therefore approximated by a nonlinear model-based constraint controller. In order to account for the uncertainty in the unmeasured state of the storage tank, the state sensitivities to the control and process measurements are propagated along with the state to obtain a state variance estimate. When the variance of the state exceeds a maximum threshold, the constraint control algorithm automatically degrades into a fail-safe operation.
Unmanned aerial vehicles (UAVs) are excellent platforms for detecting and tracking objects of interest on or near the ground due to their vantage point and freedom of movement. This paper presents a cooperative vision...
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ISBN:
(纸本)9783540743545
Unmanned aerial vehicles (UAVs) are excellent platforms for detecting and tracking objects of interest on or near the ground due to their vantage point and freedom of movement. This paper presents a cooperative vision-based estimation and tracking system that can be used in such situations. The method is shown to give better results than could be achieved with a single UAV, while being robust to failures. In addition, this method can be used to detect, estimate and track the location and velocity of objects in three dimensions. This real-time, vision-based estimation and tracking algorithm is computationally efficient and can be naturally distributed among multiple UAVs. This chapter includes the derivation of this algorithm and presents flight results from several realtime estimation and tracking experiments conducted on MIT's Real-time indoor Autonomous Vehicle test ENvironment (RAVEN).
Model Predictive control (MPC) originated in the late seventies and has developed considerably since then. The term Model Predictive control does not designate a specific control strategy but rather an ample range of ...
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This paper presents a Receding Horizon control (RHC) algorithm to the problem of on-line flight path optimization for aircraft in a dynamic Free-Flight (FF) environment. The motivation to introduce the concept of RHC ...
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ISBN:
(纸本)9783540726982
This paper presents a Receding Horizon control (RHC) algorithm to the problem of on-line flight path optimization for aircraft in a dynamic Free-Flight (FF) environment. The motivation to introduce the concept of RHC is to improve the robust performance of solutions in a dynamic and uncertain environment, and also to satisfy the restrictive time limit in the real-time optimization of this complicated air traffic control problem. Compared with existing algorithms, the new algorithm proves more efficient and promising for practical applications.
In this work, two methods based on a nonlinear MPC scheme are proposed to solve close-loop stochastic dynamic optimization problems assuring both robustness and feasibility with respect to output constraints. The main...
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ISBN:
(纸本)9783540726982
In this work, two methods based on a nonlinear MPC scheme are proposed to solve close-loop stochastic dynamic optimization problems assuring both robustness and feasibility with respect to output constraints. The main concept lies in the consideration of unknown and unexpected disturbances in advance. The first one is a novel deterministic approach based on the wait-and-see strategy. The key idea is here to anticipate violation of output hard-constraints, which are strongly affected by instantaneous disturbances, by backing off of their bounds along the moving horizon. The second method is a new stochastic approach to solving nonlinear chance-constrained dynamic optimization problems under uncertainties. The key aspect is the explicit consideration of the stochastic properties of both exogenous and endogenous uncertainties in the problem formulation (here-and-now strategy. The approach considers a nonlinear relation between the uncertain input and the constrained output variables.
In this paper, an alternative approach to the computation of control invariant sets for piecewise affine systems is presented. Based on two approximation operators, two algorithms that provide outer and inner approxim...
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ISBN:
(纸本)9783540726982
In this paper, an alternative approach to the computation of control invariant sets for piecewise affine systems is presented. Based on two approximation operators, two algorithms that provide outer and inner approximations of the maximal robust control invariant set are presented. These algorithms can be used to obtain a robust control invariant set for the system. An illustrative example is presented.
The paper reports on recent progress in the real-time computation of constrained closed-loop optimal control, in particular the special case of nonlinear model predictive control, of large differential algebraic equat...
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ISBN:
(纸本)9783540726982
The paper reports on recent progress in the real-time computation of constrained closed-loop optimal control, in particular the special case of nonlinear model predictive control, of large differential algebraic equations (DAE) systems arising e.g. from a MoL discretization of instationary PDE. Through a combination of a direct multiple shooting approach and an initial value embedding, a so-called "real-time iteration" approach has been developed in the last few years. One of the basic features is that in each iteration of the optimization process, new process data are being used. Through precomputation - as far as possible - of Hessian, gradients and QP factorizations the response time to perturbations of states and system parameters is minimized. We present and discuss new real-time algorithms for fast feasibility and optimality improvement that do not need to evaluate Jacobians online.
This paper presents a novel approach for nonlinear model predictive control based on the concept of passivity. The proposed nonlinear model predictive control scheme is inspired by the relationship between optimal con...
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ISBN:
(纸本)9783540726982
This paper presents a novel approach for nonlinear model predictive control based on the concept of passivity. The proposed nonlinear model predictive control scheme is inspired by the relationship between optimal control and passivity as well as by the relationship between optimal control and model predictive control. In particular, a passivity-based state constraint is used to obtain a nonlinear model predictive control scheme with guaranteed closed loop stability. Since passivity and stability are closely related, the proposed approach can be seen as an alternative to control Lyapunov function based approaches. To demonstrate its applicability, the passivity-based nonlinear model predictive control scheme is applied to control a quadruple tank system.
This article discusses why novel modelling and analysis methods are required for biological systems, presents recent advances and outlines some future challenges. In this respect, the main focus is placed upon methods...
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ISBN:
(纸本)9783540719878
This article discusses why novel modelling and analysis methods are required for biological systems, presents recent advances and outlines some future challenges. In this respect, the main focus is placed upon methods for parameter estimation and sensitivity analysis as they are encountered in systems biology.
A positive dynamical system is said to be persistent if every solution that starts in the interior of the positive orthant does not approach the boundary of this orthant. For chemical reaction networks and other model...
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ISBN:
(纸本)9783540719878
A positive dynamical system is said to be persistent if every solution that starts in the interior of the positive orthant does not approach the boundary of this orthant. For chemical reaction networks and other models in biology, persistence represents a non-extinction property: if every species is present at the start of the reaction, then no species will tend to be eliminated in the course of the reaction. This paper provides checkable necessary as well as sufficient conditions for persistence of chemical species in reaction networks, and the applicability of these conditions is illustrated on some examples of relatively high dimension which arise in molecular biology. More specific results are also provided for reactions endowed with mass-action kinetics. Overall, the results exploit concepts and tools from Petri net theory as well as ergodic and recurrence theory.
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