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The first proposition guarantees that at least one branch of the conditional statement can be chosen (recall that the square brackets around P => bl v b2 mean that the property is true in all states); the second and third propositions specify the correctness of the individual branches. Exercise 10.7. Introduce additional assertions into the following Hoare triples so that every assignment statement is bracketed by a precondition and a postcondition. Use the assignment axiom to verify the correctness of each assignment with respect to its precondition and postcondition.

20

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Figure 3.22 The effect of an electric field on the ground state energy E1 of a 200 A Gao.8Alo.2As/60 A GaAs/200 A Gao.8Alo.2As single quantum well

(a) { mxn = p }

was found that the ground state energy over the range of fields investigated, could be represented very well by the parabola:

{ 0 < w i A O ^ n A gcd(m,n)=C }

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The design of fuzzy controllers is one of the largest application areas of fuzzy set theory. Where fuzzy logic is frequently described as computing with words rather than numbers, fuzzy control is described as control with sentences rather than equations. Thus, instead of describing the control strategy in terms of differential equations, control is expressed as a set of linguistic rules. These linguistic rules are easier understood than systems of mathematical equations. The first application of fuzzy control comes from the work of Mamdani and Assilian in 1975, with their design of a fuzzy controller for a steam engine [Mamdani et al. 1975]. The objective of the controller was to maintain a constant speed by controlling the pressure on pistons, by adjusting the heat supplied to a boiler. Since then, a vast number of fuzzy controllers have been developed for consumer products and industrial processes. For example, fuzzy controllers have been developed for washing machines, video cameras, air conditioners, etc., while industrial applications include robot control, underground trains, hydro electrical power plants, cement kilns, etc. This chapter gives a short overview of fuzzy controllers. Section 20.1 discusses the components of such controllers, while Section 20.2 overviews some types of fuzzy controllers.

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where E1(0) refers to the ground-state energy (53.310 meV) at zero field, and the electric field strength F is in units of kVcm 1. 3.13 FIELD INDUCED ANTI-CROSSINGS As a further example of electric-field-induced phenomena and the versatility of the numerical solution, consider a double quantum well, as shown in Fig. 3.15 but with the left-hand well wider than the right. This asymmetry breaks the degeneracy of the two confined states and results in the lower energy state being more localised in the wider left hand well and the higher energy state being associated with the narrower right hand well. On the addition of an electric field, the left hand side of the structure increases in potential, while the right hand side decreases, and thus the energy levels are brought closer together. A priori, it is not clear what happens in such a situation. However, the system can be solved numerically for all field points in order to reveal the particulars of the quantum mechanics. Fig. 3.23 displays the results of such a calculation. The two energy levels are brought closer together, and as the field increases their separation AE (= E 2 E 1 ), which is initially decreasing linearly, reaches a minimum

Exercise 10.8. Rather than assign the absolute value of A: to a new variable y as we did above, it may be required to update x to its absolute value. To specify such an update operation it is necessary to use a ghost variable. The program segment complete with precondition and postcondition is shown below, variable X being the ghost variable.

Figure 3.23 The two lowest energy confined states of a 200 A Gao.8 A10.2 As/60 A GaAs/60 A Gao.sAlo.2As/50 A GaAs/200 A Gao.gAlo.2As double quantum well as a function of the applied electric field

A fuzzy controller can be regarded as a nonlinear static function that maps controller inputs onto controller outputs. A controller is used to control some system, or plant. The system has a desired response that must be maintained under whatever inputs are received. The inputs to the system can, however, change the state of the system, which causes a change in response. The task of the controller is then to

{ X=\x\ }

value and then increases again. Within the linear sections, AE is merely equal to the difference in field potentials between the centres of the wells, in this case:

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