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haptic control of hydraulic machinery using proportional valves

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the closed-form inverse kinematic solution. Geometrically different regions, denoted<br />

by R ij , map to the workspace, or a point or curve on the edge <strong>of</strong> the workspace. Note<br />

that this can be done with out loss <strong>of</strong> generality for the case <strong>of</strong> both proximal and<br />

distal bucket <strong>control</strong> since both <strong>of</strong> these cases rely on calculating θ 2 and θ 3 based on<br />

P 03 in the r − z plane.<br />

The downfall <strong>of</strong> this method is that it gives priority to the position <strong>of</strong> the bucket<br />

over its orientation. Another method would be to optimize a cost function, L, that<br />

includes a bucket angle error term (see equation 3.47).<br />

L = 1 2 W r∆r 2 + 1 2 W z∆z 2 + 1 2 W φ∆φ 2 (3.47)<br />

where ∆r = r d − a c1 4, ∆z = z d − a s24 and ∆φ = φ d + π − θ 2 − θ 3 − θ 4 represent<br />

the difference between the desired and commanded position. W r , W z and W φ are<br />

weighting matrices. Since r and z are both measure distance, W r is typically equal<br />

to W z and W φ is different. Minimizing this error can be done numerically <strong>using</strong> the<br />

steepest descent method to find the optimal vector <strong>of</strong> joint angles θ 2−4 that minimize<br />

L.<br />

Ξ k+1 = Ξ k − µ∇ Ξ L T (3.48)<br />

where is the vector <strong>of</strong> joint angle that is being optimized to minimize L.<br />

⎡ ⎤<br />

θ 2 (k)<br />

Ξ k =<br />

⎢ θ 3 (k)<br />

⎥<br />

⎣ ⎦<br />

θ 4 (k)<br />

(3.49)<br />

and ∇ Ξ L T is the transpose <strong>of</strong> the gradient <strong>of</strong> L with respect to Ξ.<br />

36

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