Time Domain Neal-Smith (TDNS) criterion is an ideal quantization criterion for evaluation PIO susceptibility. The characteristic of pilot's selfadapting make it difficult to apply the criterion. In this paper, ...
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Time Domain Neal-Smith (TDNS) criterion is an ideal quantization criterion for evaluation PIO susceptibility. The characteristic of pilot's selfadapting make it difficult to apply the criterion. In this paper, sequential quadratic programming (SQP) algorithm is used for TDNS criterion, and the PIO susceptibility of an example aircraft is evaluated. The evaluation results indicate that it is practicable to evaluate PIO susceptibility by TDNS criterion with SQP algorithm.
Time Domain Neal-Smith(TDNS) criterion is an ideal method for evaluation PIO *** characteristic of pilot's self-adapting make it difficult to apply the *** this *** quadraticprogramming(SQP) algorithm is used for...
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Time Domain Neal-Smith(TDNS) criterion is an ideal method for evaluation PIO *** characteristic of pilot's self-adapting make it difficult to apply the *** this *** quadraticprogramming(SQP) algorithm is used for TDNS criterion,and the PIO susceptibility of an example aircraft is *** evaluation results indicate that it is practicable to evaluate PIO susceptibility by TDNS criterion with SQP algorithm.
This paper presents a new technique for tuning the parameters of a PID controller for load frequency control (LFC) using sequential quadratic programming (SQP) method. In this method the frequency deviation of the sys...
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ISBN:
(纸本)9781424457939
This paper presents a new technique for tuning the parameters of a PID controller for load frequency control (LFC) using sequential quadratic programming (SQP) method. In this method the frequency deviation of the system is directly utilized to tune the controller parameters. Simulations are carried out with considering the effect of generation rate constraints (GRC) and the governor limiters. Comparative results of the proposed method and a conventional PI controller show its robustness with a satisfactory response when the parameters of the system change.
In this work, shape optimization is carried out of a single link flexible revolute flexible manipulator to extremize two objective functions (static tip deflection and fundamental frequency) using sequentialquadratic...
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In this work, shape optimization is carried out of a single link flexible revolute flexible manipulator to extremize two objective functions (static tip deflection and fundamental frequency) using sequential quadratic programming (SQP) method. Robotic link is considered as an Euler-Bernoulli beam and finite element formulation is done. Newmark's scheme is used for its dynamic analysis. A comparative study of vibration suppression is carried out of uniform and shape optimized revolute robotic link under the excitation of sinusoidal/controlled torque.
A heuristic technique is developed for a nonlinear magnetohydrodynamics (MHD) Jeffery-Hamel problem with the help of the feed-forward artificial neural net- work (ANN) optimized with the genetic algorithm (GA) a...
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A heuristic technique is developed for a nonlinear magnetohydrodynamics (MHD) Jeffery-Hamel problem with the help of the feed-forward artificial neural net- work (ANN) optimized with the genetic algorithm (GA) and the sequential quadratic programming (SQP) method. The twodimensional (2D) MHD Jeffery-Hamel problem is transformed into a higher order boundary value problem (BVP) of ordinary differential equations (ODEs). The mathematical model of the transformed BVP is formulated with the ANN in an unsupervised manner. The training of the weights of the ANN is carried out with the evolutionary calculation based on the GA hybridized with the SQP method for the rapid local convergence. The proposed scheme is evaluated on the variants of the Jeffery-Hamel flow by varying the Reynold number, the Hartmann number, and the an- gles of the walls. A large number of simulations are performed with an extensive analysis to validate the accuracy, convergence, and effectiveness of the scheme. The comparison of the standard numerical solution and the analytic solution establishes the correctness of the proposed designed methodologies.
This article suggests a strategy to control semi-active suspensions of vehicles in a pro-active way to adapt to future road profiles. The control strategy aims to maximise comfort while maintaining good handling prope...
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This article suggests a strategy to control semi-active suspensions of vehicles in a pro-active way to adapt to future road profiles. The control strategy aims to maximise comfort while maintaining good handling properties. It employs suitably defined optimal control problems in combination with a parametric sensitivity analysis. The optimal control techniques are used to optimise the time-dependent damper coefficients in an electro-rheological damper for given nominal road profiles. The parametric sensitivity analysis is used to adapt the computed nominal optimal controls to perturbed road profiles in real time. The method is particularly useful for events with a low excitation frequency such as ramps, bumps, or potholes. For high-frequency excitations standard controllers are preferable;so we propose a switched open-closed-loop controller design. Various examples demonstrate the performance of the approach.
In this paper, novel computing approach using three different models of feed-forward artificial neuralnetworks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painleve equation. The...
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In this paper, novel computing approach using three different models of feed-forward artificial neuralnetworks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painleve equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models. (C) 2014 Elsevier B.V. All rights reserved.
This paper presents an exact penalty method for solving optimization problems with very general constraints covering, in particular, nonlinear programming (NLP), semidefinite programming (SDP), and second-order cone p...
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This paper presents an exact penalty method for solving optimization problems with very general constraints covering, in particular, nonlinear programming (NLP), semidefinite programming (SDP), and second-order cone programming (SOCP). The algorithm is called the sequential linear cone method (SLCM) because for SDP and SOCP the main cost of computation amounts to solving at each iteration a linear cone program for which efficient solvers are available. Restricted to NLP, SLCM is exactly a sequentialquadratic program method. Under two basic conditions which concern only the data, it is proved that the sequence of iterates is bounded. Furthermore, in particular, when the feasible set is nonempty, under two additional constraint qualification conditions, it is proved that the cluster points are stationary points. In that case, it is established also that the sequence of penalty parameters eventually stays constant, and for a particular class of data it is proved that a unit step length can be obtained.
A new computational intelligence technique is presented for solution of non-linear quadratic Riccati differential equations of fractional order based on artificial neural networks (ANNs) and sequentialquadratic progr...
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A new computational intelligence technique is presented for solution of non-linear quadratic Riccati differential equations of fractional order based on artificial neural networks (ANNs) and sequential quadratic programming (SQP). The power of feed forward ANNs in an unsupervised manner is exploited for mathematical modeling of the equation;training of weights is carried out with an efficient constrained optimization technique based on the SQP algorithm. The proposed scheme is evaluated on two initial value problems of the Riccati fractional order equation with integer and non-integer derivatives. Comparison of results with the exact solution, and with reference numerical methods demonstrates the correctness of the proposed methodology. Performance of the proposed scheme is also validated using results of statistical analysis based on a sufficiently large number of independent runs. (C) 2014 Elsevier Inc. All rights reserved.
Propeller performance is traditionally represented by a performance map that gives propeller efficiency as a function of the flight Mach number, the power coefficient C-P, and the advance ratio J. This work aims to de...
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Propeller performance is traditionally represented by a performance map that gives propeller efficiency as a function of the flight Mach number, the power coefficient C-P, and the advance ratio J. This work aims to demonstrate how this map changes when the design C-P and J change and to propose a novel map format that is able to capture the performance of different propeller designs. For this purpose, the propeller performance is simulated using a propeller lifting-line method validated for the SR3 propfan. Subsequently, the propeller model is used within a sequential quadratic programming framework to optimize the blade twist and chord distribution for different sets of design C-P and J. A complete propeller performance map is then generated for each one of the optimized designs. The results demonstrate that all the investigated propellers can be modeled by a common map, which determines separately the ideal efficiency and the viscous losses. The ideal efficiency is given in the traditional format of eta(i) = f (C-P, J), whereas the viscous losses are represented as a function of the relative variables C-P/C-Pdes and J/J(des).
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