Fig. 1 The phase portrait of the closed-loop adaptive system More

Fig. 2 The trajectory of the estimated parameter θ ^ 1 More

Fig. 3 The trajectory of the estimated parameter θ ^ 2 More

Fig. 4 The trajectory of the control input u More

Fig. 1 Schematic diagram representation of the experimental setup of the PAM system More

Fig. 2 The mechanical connection uses a pulley between double and single PAM with the measuring sensors More

Fig. 3 ( a ) The different applied voltages V s 1 and V s 2 to the proportional pressure regulator of the single PAM, ( b ) and ( c ) the applied voltage to the measured voltage characteristic of the proportional pressure regulator More

Fig. 4 ( a ) and ( b ) The displacement-to-voltage hysteresis loops of the PAM system using applied voltages ( V s 1 and V s 2 ) under different load force F L and ( c ) the maximum displacement of the PAM system as function of the load force F L More

Fig. 5 The estimated weights g q as function of the thresholds d q for each given F L j More

Fig. 6 The proposed load force dependent coefficient functions: ( a ) a j ( F L j ) , ( b ) b j ( F L j ) , ( c ) c j ( F L j ) , and ( d ) w j ( F L j ) More

Fig. 7 Comparison between the measured voltage-to-displacement hysteresis loops and the estimated voltage-to-displacement hysteresis loops using the LDPI model at load force of ( a ) F L = 0 N, ( b ) F L = 10 N, and ( c ) F L = 100 N More

Fig. 8 Comparison between the measured displacement and the estimated displacement using the LDPI model and the modeling error at load force of ( a ) F L = 0 N , ( b ) F L = 10 N , and ( c ) F L = 100 N More

Fig. 1 Sketch of a farm and harvesting robot fleet configuration More

Fig. 2 (Scenario on the left) Robot i selects unharvested row k as the new assignment. (Scenario on the right) Robot i wins the bid to help robot j and selects row( j ) as the new assignment. More

Fig. 3 Interactions among decision layers More

Fig. 4 Communications between robot i and truck in Algorithm 4 (layer 3) More