Abstract
Proposed in this paper is a model-free and chattering-free second order sliding mode control (2nd-SMC) in combination with a backpropagation neural network (BP-NN) control scheme for underwater vehicles to deal with external disturbances (i.e., ocean currents) and parameter variations caused, for instance, by the continuous interchange of tools. The compound controller, here called the neuro-sliding control (NSC), takes advantage of the 2nd-SMC robustness and fast response to drive the position tracking error to zero. Simultaneously, the BP-NN contributes with its capability to estimate and to compensate online the hydrodynamic variations of the vehicle. When a change in the vehicle’s hydrodynamics occurs, the 2nd-SMC may no longer be able to compensate for the variations since its feedback gains are tuned for a different condition; thus, in order to preserve the desired performance, it is necessary to re-tune the feedback gains, which a cumbersome and time consuming task. To solve this, a viable choice is to implement a BP-NN control scheme along with the 2nd-SMC that adds or removes energy from the system according to the current condition it is in, in order to keep, or even improve, its performance. The effectiveness of the proposed compound controller was supported by experiments carried out on a mini-ROV.
Highlights
Underwater robots are nonlinear systems that operate in complex marine environments
We present the experimental results of the proposed neuro-sliding controller thiswell section, we present experimental results of thecontrollers
The second order sliding mode control was implemented with the addressed in this paper
Summary
Underwater robots are nonlinear systems that operate in complex marine environments They are subject to ocean currents that affect their performance by following a required trajectory or keeping a desired position while carrying out specific tasks. Their performance is affected by the addition or removal of tools like robot arms and/or measurement instruments, among others, during the execution of a task because their weight and hydrodynamic parameters change . These changes are considered as external perturbations that need to be compensated for in order to achieve a desired performance [1,2]. To reduce the chattering amplitude, Sensors 2019, 19, 2943; doi:10.3390/s19132943 www.mdpi.com/journal/sensors
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