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Evolutionary optimization of interval mathematics-based design of a TSK fuzzy controller for anti-sway crane control

Smoczek J.

International Journal of Applied Mathematics and Computer Science

2013

Vol. 23, no. 4

749--759

A hybrid method combining an evolutionary search strategy, interval mathematics and pole assignment-based closed-loop control synthesis is proposed to design a robust TSK fuzzy controller. The design objective is to minimize the number of linear controllers associated with rule conclusions and tune the triangular-shaped membership function parameters of a fuzzy controller to satisfy stability and desired dynamic performances in the presence of system parameter variation. The robust performance objective function is derived based on an interval Diophantine equation. Thus, the objective of a fuzzy logic-based control scheme is to place all the closed-loop control system characteristic polynomial coefficients within desired intervals. The reproduction process in the proposed Evolutionary Algorithm (EA) is based on the arithmetical crossover, uniform and non-uniform mutation along with gene deletion/insertion mutation ensuring a diversity of genomes sizes, as well as a diversity in the parameter space of membership functions. The proposed algorithm was implemented to design a fuzzy logic-based anti-sway crane control system taking into consideration the rope length and the mass of a payload variation. The results of experiments conducted using the EA for different conditions assumed for system parameter intervals and desired closed-loop system performances are compared with results achieved using the iterative procedure which is also described in the paper.

Genetic fuzzy approach to adaptive crane control system

Smoczek J.

Journal of KONES

2012

Vol. 19, No. 4

577-584

In automated manufacturing processes the safety, precise and fast transfer of goods realized by automated material handling devices is required to raise efficiency and productivity of manufacturing process. Hence, in those industrial branches where cranes are extensively used the problem of an anti-sway crane control is especially important to speed-up the time of transportation operations and ensures the safe and effective transportation operations. The precise positioning of a cargo requires controlling the speed of crane motion mechanisms to reduce the sway of a payload. Moreover, the anti-sway crane control scheme involves applying the adaptive techniques owing to the nonlinearities of a system that comes especially from stochastic variation of rope length on which a payload is suspended and mass of this payload. The paper provides the design method of an adaptive control system for a planar model of crane. The control system is based on the gain scheduling control scheme created using fuzzy logic controller with Takagi-Sugeno-Kang-type fuzzy implications. The design process of a gain scheduling control system consists in selecting such a suitable set of operating points at which the linear controllers are determined that interpolation control scheme ensures the expected control quality within the known range of nonlinear system parameters changes, when those parameters vary in relation to the exogenous variables: rope length and mass of a payload. The method that is proposed in this paper to solve the problem of designing the fuzzy gain scheduling crane control system for minimum set of operating points is based on the pole placement method and genetic algorithm.