Robust trajectory tracking control of non-holonomic wheeled mobile robots using an adaptive fractional order parallel fuzzy PID controller
Non-holonomic wheeled mobile robots (WMRs) are highly uncertain, multi-input multi-output (MIMO), non-linear dynamic systems that are expected to perform under varying environment and structural reservations. An Adaptive Fractional Order Parallel Fuzzy Proportional-Integral-Derivative (AFO−PFPID) controller is proposed and investigated on WMR to meet the above challenges. Computer simulations were carried out under the effects of dynamic parameter variations, noise, forced displacement, time delay, and uncertainty in the pose to thoroughly assess the controller's performance.
Further, to evaluate its relative assessment, the AFO−PFPID controller's performance is compared with its integer counterpart Adaptive Integer Order Parallel Fuzzy Proportional-Integral-Derivative (AIO−PFPID) controller. Both the controllers were tuned with the Multi-Objective Grey Wolf Optimization Algorithm to minimize the positional and velocity profile errors with an overall goal to attain effective trajectory tracking. Though both the controllers effectively performed tracking goals, the AFO−PFPID controller has offered a significantly robust performance even under the model uncertainties and disturbances. Therefore, based on the presented investigations, it is concluded that the AFO−PFPID controller is a superior control technique for non-holonomic WMRs trajectory tracking application.
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Non-holonomic wheeled mobile robots (WMRs) are highly uncertain, multi-input multi-output (MIMO), non-linear dynamic systems that are expected to perform under varying environment and structural reservations. An Adaptive Fractional Order Parallel Fuzzy Proportional-Integral-Derivative (AFO−PFPID) controller is proposed and investigated on WMR to meet the above challenges. Computer simulations were carried out under the effects of dynamic parameter variations, noise, forced displacement, time delay, and uncertainty in the pose to thoroughly assess the controller's performance.
Further, to evaluate its relative assessment, the AFO−PFPID controller's performance is compared with its integer counterpart Adaptive Integer Order Parallel Fuzzy Proportional-Integral-Derivative (AIO−PFPID) controller. Both the controllers were tuned with the Multi-Objective Grey Wolf Optimization Algorithm to minimize the positional and velocity profile errors with an overall goal to attain effective trajectory tracking. Though both the controllers effectively performed tracking goals, the AFO−PFPID controller has offered a significantly robust performance even under the model uncertainties and disturbances. Therefore, based on the presented investigations, it is concluded that the AFO−PFPID controller is a superior control technique for non-holonomic WMRs trajectory tracking application.
LINK 3 - TÌM KIẾM SÁCH/TÀI LIỆU ONLINE (GIÁ ƯU ĐÃI NHẤT)
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