A hybrid optimization algorithm based on cuckoo search and differential evolution for solving constrained engineering problems

An improved cuckoo search algorithm for the problem of electric distribution network reconfiguration

Antenna arrays are able to improve the directivity performance and reduce the cost of wireless communication systems. However, how to reduce the maximum sidelobe level (SLL) of the beam pattern is a key problem in antenna arrays. In this paper, three kinds of antenna arrays that are linear antenna array (LAA), circular antenna array (CAA) and random antenna array (RAA) are investigated. First, we formulate the SLL suppression optimization problems of LAA, CAA and RAA, respectively. Then, we propose a novel method called improved chicken swarm optimization (ICSO) approach to solve the formulated optimization problems. ICSO introduces four enhanced strategies including the local search factor, weighting factor and global search factor into the update method of conventional chicken swarm optimization (CSO) algorithm, respectively, for achieving better beam pattern optimization results of antenna arrays. Moreover, a variation mechanism is proposed to enhance the population diversity so that further improving the performance of the algorithm. We conduct simulations to evaluate the performance of the proposed ICSO for the maximum SLL suppressions of LAAs, CAAs and RAAs, and the results show that ICSO obtains lower maximum SLLs for different antenna array cases with different numbers of antenna elements compared to several other algorithms.

/pdf/sidelobe-reductions-of-antenna-arrays-via-an-improved-32tu0eardq.pdf

Sidelobe Reductions of Antenna Arrays via an Improved Chicken Swarm Optimization Approach

Lévy flight is a random walk mechanism which can make large jumps at local locations with a high probability. The probability density distribution of Lévy flight was characterized by sharp peaks, asymmetry, and trailing. Its movement pattern alternated between frequent short-distance jumps and occasional long-distance jumps, which can jump out of local optimal and expand the population search area. The metaheuristic algorithms are inspired by nature and applied to solve NP-hard problems. Lévy flight is used as an operator in the cuckoo algorithm, monarch butterfly optimization, and moth search algorithms. The superiority for the Lévy flight-based metaheuristic algorithms has been demonstrated in many benchmark problems and various application areas. A comprehensive survey of the Lévy flight-based metaheuristic algorithms is conducted in this paper. The research includes the following sections: statistical analysis about Lévy flight, metaheuristic algorithms with a Lévy flight operator, and classification of Lévy flight used in metaheuristic algorithms. The future insights and development direction in the area of Lévy flight are also discussed.

/pdf/survey-of-levy-flight-based-metaheuristics-for-optimization-2s0seh9q.pdf

Survey of Lévy Flight-Based Metaheuristics for Optimization

Cuckoo search algorithm with onlooker bee search for modeling PEMFCs using T2FNN

Display Omitted We presented a novel modified cuckoo search algorithm (NMCSA) for optimal placement of actuators problems.The proposed NMCSA employs a novel adaptive strategy to balance exploration and exploitation, which lead to achieve a more rapid and efficient algorithm.Actuators located in positions determined by proposed algorithm can effectively reduce control spillover.The NMCSA is compared with state-of-the algorithms and their variants. Computational results show that the NMCSA outperforms with many other metaheuristics in the literature. This paper proposes a novel modified cuckoo search algorithm (NMCSA) to solve optimal placement of actuators (OPA) for active vibration control. The purpose of OPA is to minimize control spillover effect and maximize the control force applied to the desired modes. To achieve this objective, NMCSA first employs speed factor (SFR) and aggregation factor (AFR) for recording and analyzing the current and history information of nests. Secondly, SFR and AFR are mapped to suitable space by scale conversion factors (SCF). Thus, the NMCSA based on SCF can give adaptively actions on the step size and discovery probability pa to balance exploration and exploitation. The performance of NMCSA is confirmed by some well-known benchmark functions. Subsequently, the NMCSA is applied to solve OPA and compared with several state-of-the-art algorithms in the literature, the statistical results demonstrate that the proposed algorithm has a higher convergence speed and better search ability.

Modified cuckoo search algorithm for the optimal placement of actuators problem

The paper studies a method which uses a solid propellant microthruster array (SPMA) as an actuator to control vibration of solar panels and the attitude of a satellite simultaneously. To so...

Active Vibration Control of Flexible Satellites Using Solid Propellant Microthruster Array

Cold gas propulsion system is the most widely used propulsion technology for Drag-free spacecraft at home and abroad. The flow output is generated by feedback-loop control of valve opening of piezoelectric proportional valve, and then the micro flow is converted into micro thrust. Due to the inherent nonlinear characteristics of piezoelectric actuator in piezoelectric proportional valve, such as hysteresis, creep, temperature drift, as well as the mechanical structure of valve body, fluid flow, there are nonlinear factors, resulting in a nonlinear relationship between the output flow rate of the system and the driving voltage. Therefore, in order to realize control compensation, the nonlinear link in the system should be analyzed first, a reasonable mathematical model should be established. This paper analyses the structure of each link of the system and determines the nonlinear factor of the system. And analyze the reason why the existing model is not suitable for the whole model of piezoelectric proportional valve. Combined with the analysis of the theoretical model, an improved BW model is proposed: the linear ARX model is combined with the BW hysteresis component model. The order information of the linear component is determined through the system structure identification, and the unknown parameters in the model are identified by the genetic algorithm, and the curve mean absolute error of fitting is 0.2643 mg/s, and the goodness of fit is 97%. Furthermore, the proposed soft measurement method of valve core displacement can reconstruct the displacement output of valve core without adding displacement sensor, which is used for the design of feedback-loop controller. The system model established in this paper has guiding significance for the controller design of the cold gas propulsion system, the structural improvement of the piezoelectric proportional valve and the nonlinear compensation.

Identification modeling of micro thrust cold gas propulsion system

The high-precision control of picosatellites and nanosatellites has always plagued the astronautics field. Aiming to change the status quo of the actuators not being able to meet the high-precision attitude control of picosatellites and nanosatellites, this article formulates a control allocation strategy for picosatellites and nanosatellites using the solid propellant microthruster array (SPMA). To solve the problem of the diversity and complexity of ignition combinations brought about by the high integration of the SPMA, the energy consumption factor of the optimal allocation is established, and the relationships of the array’s energy consumption factor, the control accuracy, the number, and the ignition combinations of the thruster array are deduced. The optimization objective is introduced by Sherman-Morrison formula and singular value decomposition. Thus, the energy consumption problem is transformed into an integer programming problem, acquiring the control allocation strategy and the optimal thruster energy. Simulation results show that the proposed algorithm can effectively reduce the thrust energy consumption and improve the precision control, demonstrating the feasibility and efficiency of the proposed algorithm for picosatellites and nanosatellites.

/pdf/allocation-optimization-strategy-for-high-precision-control-1q6zxxgwm9.pdf

Allocation Optimization Strategy for High-Precision Control of Picosatellites and Nanosatellites

Actuator configuration and optimization play a vital role in active control of vibration. This article formulates an actuator position optimization strategy for active control system of solar panel...

Optimal placement of actuators for active vibration control using a novel adaptive cuckoo search

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