This paper presents a hybrid differential evolution (DE) with quantum-behaved particle swarm optimization (QPSO) for the unmanned aerial vehicle (UAV) route planning on the sea. The proposed method, denoted as DEQPSO, combines the DE algorithm with the QPSO algorithm in an attempt to further enhance the performance of both algorithms. The route planning for UAV on the sea is formulated as an optimization problem. A simple method of pretreatment to the terrain environment is proposed. A novel route planner for UAV is designed to generate a safe and flyable path in the presence of different threat environments based on the DEQPSO algorithm. To show the high performance of the proposed method, the DEQPSO algorithm is compared with the real-valued genetic algorithm, DE, standard particle swarm optimization (PSO), hybrid particle swarm with differential evolution operator, and QPSO in terms of the solution quality, robustness, and the convergence property. Experimental results demonstrate that the proposed method is capable of generating higher quality paths efficiently for UAV than any other tested optimization algorithms.

Pseudorandom binary sequences play a significant role in many fields, such as error control coding, spread spectrum communications, and cryptography. In recent years, chaotic system is regarded as an important pseudorandom source in the design of pseudorandom bit generators (PRBGs). Among them, most are based on one or more fixed chaotic systems, and the generated binary sequences come to be stationary. However, these kinds of chaotic PRBGs can be attacked by reconstructing the phase space or using some statistical analysis methods. In this study, a scheme for chaotic PRBG based on non‐stationary logistic map is proposed. The authors design a dynamic algorithm to change the driven parameter sequence (not random) into a random‐like sequence. The variable parameters disrupt the phase space of the system, which can resist the phase space reconstruction attacks effectively. They prove that the non‐stationary logistic map is still chaotic under Wiggins’ chaos definition. The numerical analysis shows that the generated binary sequences have good cryptographic properties and can pass the well‐known statistical tests. The authors’ chaotic PRBG based on non‐stationary logistic map is a novel scheme in the design of PRBG, and is more secure than the PRBGs based on fixed chaotic systems.

The dynamical degradation of digital chaotic systems (DCSs) often has serious negative influences on some digital chaos-based systems and then becomes one of the bottleneck problems stopping chaos from some applications. In this paper, we first restrict the Devaney’s chaos definition to finite state sets to describe the chaotic motion of digital systems. Then, we propose a novel control method for DCSs based on the differential mean value theorem and state feedback technology. Simulation results show the effectiveness, robustness, and superiority of the proposed method. Finally, we construct a new pseudorandom number generator (PRNG) and evaluate its randomness via NIST SP800-22 and TestU01 test suites. Statistical test results show that the proposed PRNG has high reliability of randomness, thus it can be used for cryptography and other potential applications.