Modeling and Event-Triggered Control ofMultiple 3D Tower Cranes over WSNs
Wireless control of 3D tower cranes is a topic of great industrial significance as it offers greater flexibility and lower maintenance cost. But the reduction in shared network resource utilization and the desired level of control performance against packet losses and delays are main concerns.
Our first aim is to develop a mathematical model of the 3D tower crane for the control design purpose. The second aim is to design a model-based eventtriggered controller for wireless control of multiple 3D tower cranes to asymptotically track step reference inputs. The controller and cranes are connected in a star topology over simulated wireless sensor network with IEEE 802.15.4 MAC protocol for channel access. The third aim is to numerically evaluate and compare the performance of the event-triggered controller with that of a periodic controller under network induced delays, packet dropouts and with respect to scalability and the effect of MAC protocol on the stability.
The dynamic model for the 3D tower crane has been identified through physical modeling followed by lumped parametric estimation. The proposed event-triggered control policy for tracking problem uses the integral control structure for which theoretical results have been derived using Lyapunov input-to-state stability theorem.
Under nominal network settings, the event-triggered controller reduces the network resource utilization by 4 times but achieves almost the same control performance as compared to periodic controller executions. The network cost under event-triggered control policy not only depends on the point network induced delay enters into the system, but also increases almost monotonically with it. The event-triggered control policy utilizes the lower communication cost as compared to periodic case only up to certain amount of delay in a loop and hence must only be preferred over periodic case after considering the level and location of delay in the system. Under these conditions, up to 13 crane tasks are schedulable over network under event-triggered control policy using CSMA/CA random access. All the simulations have been done in MATLAB® Simulink using TrueTime toolbox.
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