When they are applicable, gradient based optimization algorithms are the most efficient way to solve design optimization problems. Although gradient based methods are generally efficient, they can be made significantl...
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ISBN:
(数字)9781624105890
ISBN:
(纸本)9781624105890
When they are applicable, gradient based optimization algorithms are the most efficient way to solve design optimization problems. Although gradient based methods are generally efficient, they can be made significantly more so through the usage of analytic techniques to compute the necessary total derivatives. The traditional forward (direct) and reverse (adjoint) analytic techniques have computational costs that scale linearly with the number of design variables and the number of constraints, respectively. In this work, we present an application of a graph coloring algorithm to the analytic techniques for computing total derivative Jacobians in order to achieve much better computational scaling than the pure analytic methods can provide alone. A detailed theoretical explanation of how coloring algorithms interact with analytic derivative methods is presented that illustrates specific types of sparsity patterns that must be present in total derivative Jacobians in order for this coloring technique to be effective. The new technique has been implemented as a feature in the OpenMDAO framework and the implementation is demonstrated on two example problems. The performance on the example problems up to 50% reduction in compute cost for optimizations with bi-directional coloring compared to traditional constraint aggregation. Additionally, the results show how coloring technique alleviates some of the numerical difficulties that constraint aggregation can cause, leading to the ability to solve larger problems. It is expected that the new method will have wide applicability to multidisciplinary optimization problems, and that its availability in OpenMDAO will offer significant computational savings for users without the need for them to implement the coloring algorithm themselves.
In order to improve the convergence and calculate optimal results reliably and accurately, a trust-region algorithm based on global sequential quadratic programming (SQP) Is presented for reactive power optimization. ...
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ISBN:
(纸本)9781424404926
In order to improve the convergence and calculate optimal results reliably and accurately, a trust-region algorithm based on global sequential quadratic programming (SQP) Is presented for reactive power optimization. This method combines global SQP with trust-region method. The method of decomposed inaccurate direction component is adopted to compute trust-region sub problem to guarantee feasible region of this sub problem is not null. The penalty parameter is effectively regulated in Merit Function to avoid the Marotos Effect. This example of the computation shows that this algorithm has global convergence and is fast, accurate and reliable.
In this paper, the flight control system of a flying-wing aircraft is designed. Significant dynamic nonlinearity and control redundancy are main problems for a flying-wing aircraft. As the over-actuated system and dyn...
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ISBN:
(纸本)9781479928255;9781479928279
In this paper, the flight control system of a flying-wing aircraft is designed. Significant dynamic nonlinearity and control redundancy are main problems for a flying-wing aircraft. As the over-actuated system and dynamic nonlinearity, the flight control system is divided into two parts: control laws and control allocation. Nonlinear dynamic inversion is used to design the control laws to generate control moments as the commands of control allocator. Because the relationship between moment and effector deflection is nonlinear, the nonlinear control allocation based on SQP is designed. The nonlinear control allocation can reduce the errors between commands and responses of control moments.
We introduce some methods for constrained nonlinear programming that are widely used in practice and that are known under the names SQP for sequential quadratic programming and SCP for sequential convex programming. I...
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ISBN:
(纸本)1402077602
We introduce some methods for constrained nonlinear programming that are widely used in practice and that are known under the names SQP for sequential quadratic programming and SCP for sequential convex programming. In both cases, convex subproblems are formulated, in the first case a quadraticprogramming problem, in the second case a separable nonlinear program in inverse variables. The methods are outlined in a uniform way and the results of some comparative performance tests are listed. We especially show the suitability of sequential convex programming methods to solve some classes of very large scale nonlinear programs, where implicitly defined systems of equations seem to support the usage of inverse approximations. The areas of interest are structural mechanical optimization, i.e., topology optimization, and optimal control of partial differential equations after a full discretization. In addition, a few industrial applications and case studies are shown to illustrate practical situations under which the codes implemented by the authors are in use.
In this paper, a filter-trust-region method is used in nonlinear model predictive control (NMPC) problem. By means of simultaneous approach based on nonlinear programming, an SQP sub-problem, which treats the iterate ...
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ISBN:
(纸本)9789881563811
In this paper, a filter-trust-region method is used in nonlinear model predictive control (NMPC) problem. By means of simultaneous approach based on nonlinear programming, an SQP sub-problem, which treats the iterate step Delta u as an optimal variable, is built. After that, a trust region quadraticprogramming approach is used to solve the sub-problem, and the filter method is used to decide whether the trial point is better or not as an approximate solution to the optimization problem. And the Hessian matrix update method can also keep the sparse structure which is used to reduce the computational complexity. At last, the simulation result proves that the nonlinear predictive control algorithm based on filter-trust-region SQP method can get feasible solution within limited iterations at each time instant.
Camera system calibration and related problems are considered as least squares parameter estimation problems based on error-in-variables regression models. The interrelationship between different methods for solving t...
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ISBN:
(纸本)0819431125
Camera system calibration and related problems are considered as least squares parameter estimation problems based on error-in-variables regression models. The interrelationship between different methods for solving these problems is investigated. In addition, the origin and interrelationship of some approximate methods is also discussed.
This paper presents a new trust-region algorithm based on global sequential quadratic programming (SQP) for reactive power optimization. This method is not only reliable and accurate which is similar to SQP, but is al...
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ISBN:
(纸本)0780392302
This paper presents a new trust-region algorithm based on global sequential quadratic programming (SQP) for reactive power optimization. This method is not only reliable and accurate which is similar to SQP, but is also global convergent to trust-region search method. To guarantee feasible region of this sub problem is not null, inaccurate direction component decomposed method is adopted to compute trust-region sub problem. In order to avoid the Marotos Effect, the penalty parameter is effectively regulated in Merit Function. This example of the computation shows that this algorithm has global convergence and is fast, accurate and reliable.
The purpose of this paper is to present a fuel-optimal low-thrust transfer problem and a convex approach that can be utilized to identify an optimal solution in real time. In our previous work, two slack variables wer...
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ISBN:
(数字)9781624105951
ISBN:
(纸本)9781624105951
The purpose of this paper is to present a fuel-optimal low-thrust transfer problem and a convex approach that can be utilized to identify an optimal solution in real time. In our previous work, two slack variables were introduced to aid in reducing the coupling of the control and state variables. This proves useful in transforming the problem into a convex optimization problem. The main contribution of this paper is that the original optimal control problem can be solved without the use of one of the previously defined slack variables. After eliminating one of these slack variables, the methodology developed in our previous work is followed. In this process the control and state variables are partially decoupled, the control constraints are convexified, and the original problem is translated into a sequence of convex optimization problems. The solution can then be found utilizing interior-point methods. The success and accuracy of this newly developed method is shown through numerical simulations of a minimum-fuel Earth-to-Mars low-thrust transfer problem. The results are compared to the effectiveness of the previous form of this solution process and analyzed for relative performance and efficiency.
This paper provides a solution to the optimal trajectory planning problem in target localisation for multiple heterogeneous robots with bearing-only sensors. The objective here is to find robot trajectories that maxim...
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ISBN:
(纸本)0780389123
This paper provides a solution to the optimal trajectory planning problem in target localisation for multiple heterogeneous robots with bearing-only sensors. The objective here is to find robot trajectories that maximise the accuracy of the locations of the targets at a prescribed terminal time. The trajectory planning is formulated as an optimal control problem for a nonlinear system with a gradually identified model and then solved using nonlinear Model Predictive Control (MPC). The solution to the MPC optimisation problem is computed through Exhaustive Expansion Tree Search (EETS) plus sequential quadratic programming (SQP). Simulations were conducted using the proposed methods. Results show that EETS alone performs considerably faster than EETS+SQP with only minor differences in information gain, and that a centralised approach outperforms a decentralised one in terms of information gain. We show that a centralised EETS provides a near optimal solution. We also demonstrate the significance of using a matrix to represent the information gathered.
In this paper, modal control was used to control the active suspension of a quarter-car model. Modal control can be designed to alter the dynamics of any mode of a system without disturbing the remaining modes. Theref...
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ISBN:
(纸本)9781728137872
In this paper, modal control was used to control the active suspension of a quarter-car model. Modal control can be designed to alter the dynamics of any mode of a system without disturbing the remaining modes. Therefore, in this study, modal control was used to alter the complex eigenvalue of the body-bounce mode of a quarter-car suspension model and thereby by optimizing a measure of the frequency response functions from road disturbance to sprung and unsprung mass displacements, the ride-comfort of a vehicle was improved. It has been shown that modal control can be used in a direct manner to change the dynamics of a vehicle suspension i.e. soft suspension, stiff suspension depending on the driver attitude that affects the vehicle stability and road conditions i.e. urban driving, off-road driving.
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