Abstract
Hydraulic actuator becomes an increasingly concerned driver for human-like robots. However, its dynamic performance under the control should be still further improved because hydraulic system is a typical nonlinearity system. Interval type-2 fuzzy logic controller is an advanced control method featured with high performance to deal with uncertain and nonlinear dynamics, so designing an interval type-2 fuzzy logic controller for the control of hydraulic is a feasible method. In this article, an improved drone squadron optimization-based approach is proposed to optimize interval type-2 fuzzy logic controller parameters. To verify the feasibility and priority of improved drone squadron optimization, a comparison on three different typical plants including proportional-derivative (PD) system, proportional-integral (PI) system, and PI nonlinear system between improved drone squadron optimization and other meta-heuristic algorithms is carried out. Simulation results demonstrate that improved drone squadron optimization not only gets an appropriate interval type-2 fuzzy logic controller for system control but also outperforms other popular algorithms in accuracy of performance.
Highlights
In recent years, more and more legged robots have chosen hydraulic actuator as their drivers for the reason that hydraulic actuator can provide high power within limited size.[4]
The interval type-2 FLC (IT2FLC) used in this article is introduced, and the parameter of this IT2FLC will be optimized by DSO, GA, differential evolution (DE), and so on
improved drone squadron optimization (IDSO) is applied to designing an IT2FLC for control of different systems, with hydraulic cylinder included
Summary
More and more legged robots (such as ATLAS and Big Dog from Boston Dynamics[1,2] and HyQ from Italy Polytechnic3) have chosen hydraulic actuator as their drivers for the reason that hydraulic actuator can provide high power within limited size.[4] Hydraulic actuator is a typical nonlinear system, and conventional linear controller such as proportional-integral-derivative (PID) may not perform well in hydraulic system.[5] there is an increasing demand of applying nonlinear controller to hydraulic actuator. Fuzzy logic controller (FLC) is a nonlinear controller which has been applied in various situations,[6] such as classification and wireless sensor,[7] control of robots,[8,9] and hydraulic system.[10] Recently, there is an increasing focus on the interval type-2 FLC (IT2FLC). IT2FLC is selected for the control of our hydraulic system, and expected to perform well in this study
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