This paper presents a new result in the analysis and implementation of path constraints in optimal control problems (OCPs). The scheme uses the well-known concept of discretizing path constraints on a finite number of...
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This paper presents a new result in the analysis and implementation of path constraints in optimal control problems (OCPs). The scheme uses the well-known concept of discretizing path constraints on a finite number of points, yielding a set of interior-time point constraints replacing the original path constraints. The approach replaces the original OCP by a sequence of OCPs which is shown to converge in a finite number of steps to the solution of the original path constrained problem with c-accuracy. Numerical results, verifying the theoretical analysis, are presented. The method is shown to be effective and promising for future applications, particularly in control vector parameterization implementations. (C) 2004 Elsevier Ltd. All rights reserved.
In this work we present an adaptive parameterization strategy for the so-called sequential solution approach where the optimization problem is approximated by a nonlinear program (NLP) by parameterization of the contr...
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In this work we present an adaptive parameterization strategy for the so-called sequential solution approach where the optimization problem is approximated by a nonlinear program (NLP) by parameterization of the control variables only. The proposed method is embedded into a solution methodology where a hierarchy of successively refined finite dimensional optimization problems are solved. Information on the solution of the coarser approximation is used to construct a fully adaptive, problem dependent parameterization. The adaptation is built on a multiscale setting involving wavelets. We demonstrate examplarily that the adaptive parameterization is more efficient and robust compared with a uniform parameterization of comparable accuracy. (C) 2000 Elsevier Science Ltd. All rights reserved.
In this work we present an adaptive parameterization strategy for the so-called sequential solution approach where the optimization problem is approximated by a nonlinear program (NLP) by parameterization of the contr...
详细信息
In this work we present an adaptive parameterization strategy for the so-called sequential solution approach where the optimization problem is approximated by a nonlinear program (NLP) by parameterization of the control variables only. The proposed method is embedded into a solution methodology where a hierarchy of successively refined finite dimensional optimization problems are solved. Information on the solution of the coarser approximation is used to construct a fully adaptive, problem dependent parameterization. The adaptation is built on a multiscale setting involving wavelets. We demonstrate examplarily that the adaptive parameterization is more efficient and robust compared with a uniform parameterization of comparable accuracy. (C) 2000 Elsevier Science Ltd. All rights reserved.
A nonlinear control system integrating an off-line optimizer and a nonlinear MPC controller is developed to perform optimal grade transition operations at the industrial polyolefin reactors. In this paper, the details...
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A nonlinear control system integrating an off-line optimizer and a nonlinear MPC controller is developed to perform optimal grade transition operations at the industrial polyolefin reactors. In this paper, the details of the optimizer are given: The sequential nonlinear programming is performed in the optimizer by employing control vector parameterization method together with sensitivity analysis. The switching times (i.e. times of changing in the input actions) can be also optimized by new formulation and a modification in trial functions. The simulation result illustrates the capability of the control system with the proposed optimizer. (C) 2000 Elsevier Science Ltd. All rights reserved.
A nonlinear control system integrating an off-line optimizer and a nonlinear MPC controller is developed to perform optimal grade transition operations at the industrial polyolefin reactors. In this paper, the details...
详细信息
A nonlinear control system integrating an off-line optimizer and a nonlinear MPC controller is developed to perform optimal grade transition operations at the industrial polyolefin reactors. In this paper, the details of the optimizer are given: The sequential nonlinear programming is performed in the optimizer by employing control vector parameterization method together with sensitivity analysis. The switching times (i.e. times of changing in the input actions) can be also optimized by new formulation and a modification in trial functions. The simulation result illustrates the capability of the control system with the proposed optimizer. (C) 2000 Elsevier Science Ltd. All rights reserved.
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