We explore properties of nonlinear programming problems (NLPs) that arise in the formulation of NMPC subproblems and show their influence on stability and robustness of NMPC. NLPs that satisfy linear independence cons...
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We explore properties of nonlinear programming problems (NLPs) that arise in the formulation of NMPC subproblems and show their influence on stability and robustness of NMPC. NLPs that satisfy linear independence constraint qualification (LICQ), second order sufficient conditions (SOSC) and strict complementarity (SC), have solutions that are continuous and differentiable with perturbations of the problem data. As a result, they are important prerequisites for nominal and ISS stability of NMPC controllers. Moreover, we show that ensuring these properties is possible through reformulation of the NLP subproblem for NMPC, through the addition of l1 penalty and barrier terms. We show how these properties also establish ISS of related sensitivity-based NMPC controllers, such as asNMPC and amsNMPC. Finally, we demonstrate the impact of our reformulated NLPs on several examples that have shown nonrobust performance on earlier NMPC strategies.
As a dynamic driving process,lane change behavior involves the longitudinal and lateral motion of lane changing *** is a strong coupling effect between longitudinal and lateral motion,so it is difficult to achieve ide...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
As a dynamic driving process,lane change behavior involves the longitudinal and lateral motion of lane changing *** is a strong coupling effect between longitudinal and lateral motion,so it is difficult to achieve ideal control effect by single *** paper constructs a scene in which vehicles accelerate to change lanes on slippery roads,and longitudinal safety model is introduced to measure the longitudinal safety of vehicle following lane changing *** the side-slip phenomenon of lane change vehicles on slippery roads,the classical vehicle "bicycle" model and fixed tire cornering-stiffness are used to evaluate the tire force of vehicles on slippery roads to ensure the lateral safety of lane change *** nonlinear programing problem of lane-change trajectory planning is established,and the comparison of three solutions is given to plan the optimal lateral and longitudinal lane change acceleration for the *** simulation results show that the planned lane change trajectory meet the longitudinal and lateral safety *** considering the lateral and longitudinal coupling effects,the safety and rationality of lane changing on slippery pavement can be improved,and the deficiency of the existing lane changing trajectory planning model that does not consider the risk of sideslip can be made up.
The preliminary design process of manned or unmanned aircraft includes aircraft performance in trim flight. In this paper, a trim algorithm for computing flight-states and control inputs in trim flight is implemented ...
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ISBN:
(数字)9781624105982
ISBN:
(纸本)9781624105982
The preliminary design process of manned or unmanned aircraft includes aircraft performance in trim flight. In this paper, a trim algorithm for computing flight-states and control inputs in trim flight is implemented using a nonlinear optimization method for the propeller-driven-electric-powered unmanned air vehicle (UAV) which is designed and manufactured at Flight Laboratory IIT Kanpur. The sequential quadratic programming method (SQP) is adopted to perform the numerical analysis in three flight regimes, namely: steady-straight-level flight (SSLF), level turn flight (LTF) and climb turn flight (CTF). Analytical validation of numerical results for bank angle in LTF adds the novelty to this work. Additionally, numerical analysis reveals the SQP method takes less computation time than compared to a gradient descent method.
Supplier selection and inbound transport are among the main levers of the supply chain design and performance evaluation. Supplier selection decision is largely studied in the literature but little attention is given ...
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ISBN:
(纸本)9781467384803
Supplier selection and inbound transport are among the main levers of the supply chain design and performance evaluation. Supplier selection decision is largely studied in the literature but little attention is given to the transportation aspect in this decision. In this paper, a non-linear programming model is proposed to simultaneously determine the optimal number of suppliers to select and the order quantities to allocate to them, taking into account the transportation policies. The product bought from supplier can be shipped directly or via consolidation terminal to the buyer. Total logistics cost is the objective to minimize in the model, under suppliers, buyer and transportation constraints. A comprehensive example is provided to illustrate the model under some scenarios.
In this paper, we present a mid-level collision avoidance algorithm for autonomous surface vehicles (ASVs) based on model predictive control (MPC) using nonlinear programming. The algorithm enables avoidance of both s...
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ISBN:
(纸本)9781509021826
In this paper, we present a mid-level collision avoidance algorithm for autonomous surface vehicles (ASVs) based on model predictive control (MPC) using nonlinear programming. The algorithm enables avoidance of both static and moving obstacles, and following of a desired nominal trajectory if there is no danger of collision. We compare two alternative objective functions, where one is a quadratic function and the other is a nonlinear function designed to produce maneuvers observable for other vessels in compliance with rule 8 of the International Regulations for Preventing Collisions at Sea (COLREGS). The algorithm is implemented in the CASADI framework and uses the IPOPT solver. The performance of the algorithm is evaluated through simulations which show promising results. Furthermore, the algorithm is considered computationally feasible to run in real time. This algorithm serves as a base algorithm for further development in order to ensure full COLREGS compliance.
In this article, a complex nonlinear programming problem with objective function coefficients characterized by neutrosophic numbers and fuzzy inequalities constraints is considered. Using the score function definition...
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In this article, a complex nonlinear programming problem with objective function coefficients characterized by neutrosophic numbers and fuzzy inequalities constraints is considered. Using the score function definition, the model is converted into the corresponding crisp model with fuzzy inequalities, which can be further partitioned into two real sub-models based on the Lexicographic order. A fuzzy programming approach is applied to each sub-problem by introducing the membership functions. Linear membership function is used to obtain optimal compromise solution. A numerical experimentation is performed for the sake of the suggested approach for illustration.
This paper presents a new particle swarm optimization method through the concept of complex networks for nonlinear programming problems. The purpose of this paper is to clarify the impact of the network structure betw...
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ISBN:
(纸本)9781467327435;9781467327428
This paper presents a new particle swarm optimization method through the concept of complex networks for nonlinear programming problems. The purpose of this paper is to clarify the impact of the network structure between individuals on the solution performance. Realizing diversification and intensification of search processes, a new solution method using the ideas of complex networks is introduced. Illustrative numerical examples are provided to demonstrate the feasibility and efficiency of the proposed method.
The effectiveness of four active-set logics, Kelley's dual-violator rule, Sargent's worst-violator rule, Goldfarb's rule and Das' logic has been studied for three optimization processes of Newton, quas...
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NLPQL is a FORTRAN implementation of a sequential quadratic programming method for solving nonlinearly constrained optimization problems with differentiable objective and constraint functions. At each iteration, the s...
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In this paper we describe an algorithm for solving nonlinear nonconvex programming problems, which is based on the interior point approach. The main theoretical results concern direction determination and step-length ...
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In this paper we describe an algorithm for solving nonlinear nonconvex programming problems, which is based on the interior point approach. The main theoretical results concern direction determination and step-length selection. We split inequality constraints into active and inactive parts to overcome problems with instability. Inactive constraints are eliminated directly, whereas active constraints are used for defining a symmetric indefinite linear system. Inexact solution of this system is obtained iteratively using indefinitely preconditioned conjugate gradient method. Theorems confirming efficiency of the indefinite preconditioner are introduced. Furthermore, a new merit function is defined and a filter principle is used for step-length selection. The algorithm was implemented in the interactive system for universal functional optimization UFO. Results of numerical experiments are reported.
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