Abstract
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. With only the input and output data available, an equivalent identification is formulated by a multi-input fuzzy rule emulated network. An online-learning algorithm is proposed to tune all adjustable parameters by using convergence analysis. Using the equivalent model, a controller is developed when the convergence of the tracking error and internal signals can be guaranteed. An experimental system validates the performance of the proposed scheme. Furthermore, the comparative results are also included, to demonstrate the advantage of the proposed controller.
Highlights
Many commercial robotic systems are managed by closed architectures
By using only the input/output data, the design of model-free adaptive controllers (MFAC) based on the data-driven concept was established by linearization models that require the existence of a pseudo-partial derivative and a non-zero change of control effort [11,12]
By using only the input/output data set of the robotic system, the equivalent model has been developed by Multi-input Fuzzy Rules Emulated Network (MiFREN), where the convergence of the model error and adjustable parameter have been established
Summary
Many commercial robotic systems are managed by closed architectures. To expand the performance of closed-architecture robots, macro-mini approaches have been utilized, such as in [1,2]. By using only the input/output data, the design of MFAC based on the data-driven concept was established by linearization models that require the existence of a pseudo-partial derivative and a non-zero change of control effort [11,12] Without this constraint, the control scheme for the unknown mathematical model of robotic systems for the discrete-time domain has been proposed in [13,14], by using direct IF- rules and adaptive networks, but closed-loop analysis has been limited only the convergence of the tracking error. The robotic arm ABB model IRB-1400 is driven by six VFD units, operated by a digital computer This robotic system is considered as a class of unknown discrete-time systems when the output is directly obtained by the task-multiplexer and the input is the command voltage for VFD units.
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