Control parameter design for automatic carrier landing system via pigeon-inspired optimization

Deng, Yimin; Duan, Haibin

doi:10.1007/s11071-016-2670-z

Cited by 68 publications

(21 citation statements)

References 32 publications

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“…While it has not been long since its introduction, this algorithm has been used in model improvement and application, obtaining many research results. Because the algorithm has good adaptability and high calculation accuracy, various optimizations have been carried out in the fields of unmanned aerial vehicle (UAV) formation [25], control parameter optimization [26], and image processing [27].…”

Section: Introductionmentioning

confidence: 99%

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

et al. 2020

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Pigeon-inspired optimization (PIO) is a new type of intelligent algorithm. It is proposed that the algorithm simulates the movement of pigeons going home. In this paper, a new pigeon herding algorithm called compact pigeon-inspired optimization (CPIO) is proposed. The challenging task for multiple algorithms is not only combining operations, but also constraining existing devices. The proposed algorithm aims to solve complex scientific and industrial problems with many data packets, including the use of classical optimization problems and the ability to find optimal solutions in many solution spaces with limited hardware resources. A real-valued prototype vector performs probability and statistical calculations, and then generates optimal candidate solutions for CPIO optimization algorithms. The CPIO algorithm was used to evaluate a variety of continuous multi-model functions and the largest model of hydropower short-term generation. The experimental results show that the proposed algorithm is a more effective way to produce competitive results in the case of limited memory devices.

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Section: Introductionmentioning

confidence: 99%

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

et al. 2020

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“…Although PIO was proposed recently, it has achieved a lot of research results in terms of model improvement and application. Starting from the introduction of the pigeon's autonomous homing behavior, the mechanism principle and mathematical model of the flock optimization algorithm are explained, and typical applications in the fields of drone formation [45], control parameter optimization [46], and image processing [47] are introduced.…”

Section: Introductionmentioning

confidence: 99%

A Novel Pigeon-Inspired Optimization Based MPPT Technique for PV Systems

et al. 2020

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The conventional maximum power point tracking (MPPT) method fails in partially shaded conditions, because multiple peaks may appear on the power–voltage characteristic curve. The Pigeon-Inspired Optimization (PIO) algorithm is a new type of meta-heuristic algorithm. Aiming at this situation, this paper proposes a new type of algorithm that combines a new pigeon population algorithm named Parallel and Compact Pigeon-Inspired Optimization (PCPIO) with MPPT, which can solve the problem that MPPT cannot reach the near global maximum power point. This hybrid algorithm is fast, stable, and capable of globally optimizing the maximum power point tracking algorithm. Therefore, the purpose of this article is to study the performance of two optimization techniques. The two algorithms are Particle Swarm Algorithm (PSO) and improved pigeon algorithm. This paper first studies the mechanism of multi-peak output characteristics of photovoltaic arrays in complex environments, and then proposes a multi-peak MPPT algorithm based on a combination of an improved pigeon population algorithm and an incremental conductivity method. The improved pigeon algorithm is used to quickly locate near the maximum power point, and then the variable step size incremental method INC (incremental conductance) is used to accurately locate the maximum power point. A simulation was performed on Matlab/Simulink platform. The results prove that the method can achieve fast and accurate optimization under complex environmental conditions, effectively reduce power oscillations, enhance system stability, and achieve better control results.

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“…Nieto et al [10] described a hybrid particle swarm optimization and support vector machine based model for predicting the remaining useful life of aircraft engines. By converting the parameter design problem to an optimization problem, Deng et al [11] developed a pigeon-inspired optimization algorithm to overcome difficulties in the manual parameter adjustment task. Moreover, Dou et al [12] conducted a design of the automatic carrier landing system via the Levy-flight based pigeon-inspired optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft

2019

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Coordinated aileron and rudder control is crucial to the lateral control stability augmentation of an aircraft. In this paper, a modified non-dominated sorting genetic algorithm II is proposed to not only optimize the control allocation between the aileron and rudder channels on different flying quality levels but also explore the relationships between the optimum solutions and the state variables of the aircraft. In doing so, a digital, nets-based stratification method is used to initialize the search chromosomes more evenly. To improve the search efficiency of the algorithm, crowding-distance-based interpolation and elimination strategies are developed to approach the optimum Pareto frontier as close as possible. Moreover, a dynamic depth search method is proposed to balance between the global and local explorations. Finally, the control allocation relationships between the aileron and rudder channels on different flying quality levels are illustrated. The comparative simulations on a six-degree-of-freedom Boeing 747 model are carried out to verify the feasibility of the proposed algorithm. INDEX TERMS MNSGA-II, control allocation optimization, flight control system.

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Control parameter design for automatic carrier landing system via pigeon-inspired optimization

Cited by 68 publications

References 32 publications

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station

A Novel Pigeon-Inspired Optimization Based MPPT Technique for PV Systems

A Modified NSGA-II for Solving Control Allocation Optimization Problem in Lateral Flight Control System for Large Aircraft

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