M. M. Fateh; Seyed M. Ahmadi; S. Khorashadizadeh
Abstract
TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs ...
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TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed network includes a hidden layer with one node, two inputs and a single output. In comparison with other model-free estimators such as multilayer neural networks and fuzzy systems, the proposed estimator is simpler, less computational and more effective. The weights of the RBF network are tuned online using an adaptation law derived by stability analysis. Despite the majority of previous control approaches which are the torque-based control, the proposed control design is the voltage-based control. Simulations and comparisons with a robust neural network control approach show the efficiency of the proposed control approach applied on the articulated robot manipulator driven by permanent magnet DC motors.
Alireza Khosravi; Alireza Alfi; Amir Roshandel
Abstract
There are two significant goals in teleoperation systems: Stability and performance. This paper introduces an LMI-based robust control method for bilateral transparent teleoperation systems in presence of model mismatch. The uncertainties in time delay in communication channel, task environment and model ...
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There are two significant goals in teleoperation systems: Stability and performance. This paper introduces an LMI-based robust control method for bilateral transparent teleoperation systems in presence of model mismatch. The uncertainties in time delay in communication channel, task environment and model parameters of master-slave systems is called model mismatch. The time delay in communication channel is assumed to be large, unknown and unsymmetric, but the upper bound of the delay is assumed to be known. The proposed method consists of two local controllers. One local controller namely local slave controller is located on the remote site to control the motion tracking and the other one is located on the local site namely local master controller to preserve the complete transparency by ensuring force tracking and the robust stability of the closed-loop system. To reduce the peak amplitude of output signal respect to the peak amplitude of input signal in slave site, the local slave controller is designed based on a bounded peak-to-peak gain controller. In order to provide a realistic case, an external signal as a noise of force sensor is also considered. Simulation results show the effectiveness of proposed control structure.
