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Summary Wireless sensor networks (WSN) have high value in the field of wireless communications. As the earliest WSN clustering protocol, Low Energy Adaptive Clustering Hierarchy (LEACH) can effectively reduce the energy consumption of data transmission in sensor networks. However, LEACH has some problems such as cluster head nodes are unevenly distributed. In this paper, a unified heuristic bat algorithm (UHBA) is proposed to optimize elections in cluster heads. This algorithm guarantees that the election of cluster heads can freely transform both global search and local search. Meanwhile, comparing with several other variants of the bat algorithm in CEC2013 test suite, it can be seen from results that UHBA has better performance. Moreover, the application of the algorithm on LEACH is better than other algorithms, which further proves that the algorithm has better results.

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Design of an effective and efficient fractional order PID (FOPID) controller for an industrial control system to obtain high-quality performances is of great theoretical and practical significance. This paper presents a novel real-coded extremal optimization algorithm with multi-non-uniform mutation called RCEO-FOPID to design FOPID controllers. The key idea behind the proposed algorithm is the population-based iterated optimization, which consists of generation of a real-coded random initial population by encoding the parameters of a FOPID controller into a set of real values, evaluation of the individual fitness by using a novel and reasonable control performance index, generation of a new population based on multi-non-uniform mutation and updating the population by accepting the new population unconditionally. The proposed RCEO algorithm for the design of FOPID controller is relatively simpler than these reported popular evolutionary algorithms, e.g., genetic algorithm (GA), particle swarm optimization (PSO), chaotic anti swarm (CAS) due to its fewer adjustable parameters and only with selection and mutation operators. Furthermore, extensive simulation results on automatic voltage regulator system and multivariable control system have shown that the proposed RCEO-based FOPID controller is superior to other reported evolutionary algorithms-based FOPID and PID controllers in terms of accuracy and robustness.

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