This paper exploits a basic connection between sequential quadratic programming and Riemannian gradient optimization to address the general question of selecting a metric in Riemannian optimization, in particular when...
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This paper exploits a basic connection between sequential quadratic programming and Riemannian gradient optimization to address the general question of selecting a metric in Riemannian optimization, in particular when the Riemannian structure is sought on a quotient manifold. The proposed method is shown to be particularly insightful and efficient in quadratic optimization with orthogonality and/or rank constraints, which covers most current applications of Riemannian optimization in matrix manifolds.
In this paper, we consider device-to-device (D2D) communications as an underlay to cellular networks over both licensed and unlicensed spectrums, where long-term evolution (LTE) users utilize the spectrum orthogonally...
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In this paper, we consider device-to-device (D2D) communications as an underlay to cellular networks over both licensed and unlicensed spectrums, where long-term evolution (LTE) users utilize the spectrum orthogonally while D2D users share the spectrum with LTE users. In the system, each LTE and D2D user can access the licensed or unlicensed band for communications. To maximize the total throughput of the system, we leverage stochastic geometry to derive the throughput for each kind of user by modeling the deployment of users as Poisson point processes (PPPs), and investigate the spectrum access problem for these users. Since the problem is NP-hard, we propose a sequential quadratic programming (SQP)-based algorithm to obtain the corresponding suboptimal solutions. Theoretically, we evaluate the system performance by analyzing the throughput regions. Simulation results validate the accuracy of the geometric analysis and verify the effectiveness of the proposed algorithm.
In this paper, we study the problem of technical transient gas network optimization, which can be considered a minimum cost flow problem with a nonlinear objective function and additional nonlinear constraints on the ...
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In this paper, we study the problem of technical transient gas network optimization, which can be considered a minimum cost flow problem with a nonlinear objective function and additional nonlinear constraints on the network arcs. Applying an implicit box scheme to the isothermal Euler equation, we derive a mixed-integer nonlinear program. This is solved by means of a combination of (i) a novel mixed-integer linear programming approach based on piecewise linearization and (ii) a classical sequentialquadratic program applied for given combinatorial constraints. Numerical experiments show that better approximations to the optimal control problem can be obtained by using solutions of the sequential quadratic programming algorithm to improve the mixed-integer linear program. Moreover, iteratively applying these two techniques improves the results even further.
As the penetration level of renewable energy sources (RESs) increases, the output power of RESs needs to be curtailed to balance the power supply and load demand. Nevertheless, depending on the curtailment control str...
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As the penetration level of renewable energy sources (RESs) increases, the output power of RESs needs to be curtailed to balance the power supply and load demand. Nevertheless, depending on the curtailment control strategy for wind power plants (WPPs), while the total amount of output power curtailment remains the same, the overall stored inertial energy within WPPs may vary. Furthermore, this stored inertial energy within WPPs can be used during disturbances to enhance frequency stability. This paper proposes a novel curtailment control strategy based on the sequential quadratic programming (SQP) optimization algorithm to effectively curtail WPPs and increase the overall stored inertial energy within WPPs. Then, the proposed solution can enhance frequency stability by providing a more inertial response from WPPs during disturbances. To verify the effectiveness of this novel curtailment control strategy, several case studies are conducted using the IEEE 39-bus system. The results show that the proposed curtailment control strategy effectively increases the stored inertial energy within WPPs while satisfying the required output power curtailment.
A comparative study of evasive strategies of an aircraft against a missile with fi?red, gravity-limited, proportional navigation is conducted for both subsonic and supersonic confrontations. A complete point-mass airc...
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A comparative study of evasive strategies of an aircraft against a missile with fi?red, gravity-limited, proportional navigation is conducted for both subsonic and supersonic confrontations. A complete point-mass aircraft model and a variable-mass missile model that includes missile dynamics are used. No linearization is required in the analysis, and all motion is constrained to a horizontal plane. sequential quadratic programming is used to solve the optimal control problem. Numerical results are presented for an early model of the F-4 fighter aircraft. In particular, the effects of varying the aircraft/missile initial velocity ratio, the missile initial heading angle, and the missile guidance time constant are determined.
We describe in this paper the study of an Earth orbital transfer with a low-thrust (typically electro-ionic) propulsion system. The objective is the maximization of the final mass, which leads to a discontinuous contr...
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We describe in this paper the study of an Earth orbital transfer with a low-thrust (typically electro-ionic) propulsion system. The objective is the maximization of the final mass, which leads to a discontinuous control with a huge number of thrust arcs. The resolution method is based on single shooting, combined to a homotopic approach in order to cope with the problem of the initial guess, which is actually critical for nontrivial problems. An important aspect of this choice is that we make no assumptions on the control structure and in particular do not set the number of thrust arcs. This strategy allowed us to solve our problem (a transfer from low Earth orbit to geosynchronous equatorial orbit, for a spacecraft with mass of 1500 kg, either with or without a rendezvous) for thrusts as low as 0.1 N, which corresponds to a one-year transfer involving several hundreds of revolutions and thrust arcs. The numerical results obtained also revealed strong regularity in the optimal control structure, as well as some practically interesting empiric laws concerning the dependency of the final mass with respect to the transfer time and maximal thrust.
This paper focuses on improving indoor Wi-Fi localization by mitigating the effect of fluctuation of received signal strength indication (RSSI). The RSSI data collected at each reference point is first transformed thr...
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This paper focuses on improving indoor Wi-Fi localization by mitigating the effect of fluctuation of received signal strength indication (RSSI). The RSSI data collected at each reference point is first transformed through translation and scaling. The BP (Back Propagation) neural network is then used to construct the ranging model using the transformed RSSI to determine the distances between the target point and each reference point. A genetic algorithm (GA) is developed to optimize the initial values of weights and biases of the BP neural network. For convenience, our proposed ranging model is denoted as GTBPD. A new localization algorithm is then proposed, which uses the GTBPD model and the sequential quadratic programming (SQP, an iterative nonlinear optimization algorithm), and the algorithm is denoted as GTBPD-LSQP for simplicity. Experiments were conducted in three areas of two different teaching buildings with complex environments. The performance of the proposed GTBPD-LSQP algorithm is evaluated and compared with four existing algorithms. The experimental results show that our proposed GTBPD-LSQP algorithm achieves significantly higher location accuracy than the four existing algorithms.
The central chilled water plant is one of the major power-consuming units of a building. Even small reductions in power consumption could achieve significant energy conservation. Hence, optimization of a chiller plant...
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The central chilled water plant is one of the major power-consuming units of a building. Even small reductions in power consumption could achieve significant energy conservation. Hence, optimization of a chiller plant is necessary for energy savings without compromising the comfort level of the end user. The present work deals with identifying the system parameters and developing a novel formulation for a chiller plant and its optimization using a hybrid optimization technique. The optimization model formulation is based on finding an optimal mix of equipment and operating parameters in the chiller plant for minimum electrical power consumption. It takes into account the performance characteristics of the chillers, cooling towers and pumps, and optimizes the energy consumed based on the required loads and the ambient atmospheric conditions. sequential quadratic programming combined with the modified branch and bound method was used to develop the hybrid optimization algorithm. A case study is presented for a typical chiller plant. The results indicate that the present optimization method could be a potential method of making energy savings.
A class of synthetic problems for testing multidisciplinary design optimization (MDO) approaches is presented. These test problems are easy to reproduce because all functions are given as closed-form mathematical expr...
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A class of synthetic problems for testing multidisciplinary design optimization (MDO) approaches is presented. These test problems are easy to reproduce because all functions are given as closed-form mathematical expressions. They are constructed in such a way that the optimal value of all variables and the objective is unity. The test problems involve three disciplines and allow the user to specify the number of design variables, state variables, coupling functions, design constraints, controlling design constraints, and the strength of coupling. Several MDO approaches were executed on two sample synthetic test problems. These approaches included single-level optimization approaches, collaborative optimization approaches, and concurrent subspace optimization approaches. Execution results are presented, and the robustness and efficiency of these approaches are evaluated for these sample problems.
The electric sail is an innovative propellantless propulsion concept that gains continuous momentum from the solar wind. In this work, the electric sail's attitude dynamics is established from a multibody perspect...
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The electric sail is an innovative propellantless propulsion concept that gains continuous momentum from the solar wind. In this work, the electric sail's attitude dynamics is established from a multibody perspective. Firstly, the dynamics of a single charged tether is described by a dumbbell model. Comparisons with an elastic multipoint model show that the dumbbell model is simpler and accurate enough to describe the motion of tether when the spin rate meets a specific lower bound. Then, the electric sail's attitude dynamics model is established through Kane's method based on the dumbbell model of the tethers. Finally, a case study is performed for the electric sail. It is shown that a 4-kmradius electric sail with 12 tethers of which the voltage is 25 kV could provide the sailcraft with a characteristic acceleration of 0.1 mm/s(2). The results also indicate that the satellite bus's acceleration oscillates with the undiminished out-of-plane swing of the electric sail, in which the period and amplitude are in inverse proportional to the spin rate and its square, respectively. Besides, a dynamical equilibrium point for system's attitude exists when the electric sail is perpendicular to the solar wind. The presented work offers a basic referential model for the real-time feedback control problems of the electric sail's attitude.
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