A New Method of Force Control for Unknown Environments

We propose a new control technique for force control on unknown environments. In particular, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling direct force controller to track the desired force by adjusting control gains based on online parameter estimation. However, the ANN is tolerant to imprecise estimation of environment parameters. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed

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