Abstract
To solve the shortcomings of existing control methods for an electromagnetic direct drive vehicle robot driver, including large speed tracking error and large mileage deviation, a new adaptive speed control method for the electromagnetic direct drive vehicle robot driver based on fuzzy logic is proposed in this paper. The electromagnetic direct drive vehicle robot driver adapts an electromagnetic linear motor as its drive mechanism. The control system structure is designed. The coordinated controller for multiple manipulators is presented. Moreover, an adaptive speed controller for the electromagnetic direct drive vehicle robot driver is proposed to achieve the accurate tracking of desired speed. Experiments are conducted using a Ford FOCUS car. Performances of the proposed method, proportional–integral–derivative, and fuzzy neural network are compared and analyzed. Experimental results demonstrate that the proposed control method can accurately track the target speed, and it can inhabit the change of speed caused by interference under different test conditions, and it has small mileage deviation, which can meet the requirements of national vehicle test standards.
Highlights
Vehicle robot driver is an intelligent industrial robot which can be equipped in a vehicle cab without any modification
National standards of emissions durability,[16] the vehicle durability emission test is performed by the electromagnetic direct drive vehicle robot driver (EDDVRD)
The test results of speed tracking control, comparison of speed tracking control and speed tracking control error comparison are shown in Figures 10–12, where the test vehicle is manipulated by the EDDVRD, respectively, using PID control method, fuzzy neural network (FNN) control method and the proposed control method
Summary
Vehicle robot driver is an intelligent industrial robot which can be equipped in a vehicle cab without any modification. Vehicle robot driver must coordinate throttle pedal, brake pedal, clutch pedal and shift level, so that it can achieve the tracking control of desired speed. Chen et al utilizes a variable parameter, proportional–integral–derivative (PID) control, to realize the speed tracking of vehicle robot driver.
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