1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135
25 |
||||||||||
|
||||||||||
Figure 3.2 - An Active Limit Cycle |
||||||||||
3. 2 |
Control Formulation |
|||||||||
The problem of choosing appropriate control perturbations to drive the entire stateof a system to a |
||||||||||
desired value is a difficult one. |
Assuming a solution does exist, the number of parameters to be |
|||||||||
determined is large for all but very simple systems (a few DOFs or less). |
Non-linearities in a |
|||||||||
system mean that over the course of a full cycle even small perturbations of certain state variables |
||||||||||
can cause large changes in final state and/or result in almost no cycle at all. |
For example, a small |
|||||||||
change in the roll angle of the ankle in a walk might cause the next foot to miss the ground completely.
|
||||||||||
individual cycles and stabilize each cycle in turn. |
Each cycle is stabilized by applying control |
|||||||||
perturbations which drive its final state to a suitable state from which to begin the next cycle. |
The |
|||||||||
motivation for using a discrete version of the system is that the discrete dynamics are much simpler to model than the continuous system and therefore, simpler to control, as we shall see shortly. |