Factors affecting the formation of MgPc nanoparticles were monitored by UV- visible spectroscopy.
The spectra showed a new Q band at I= 824 nm (nearr IR region) due to the formation of MgPc nanoparticles.
Aqueous suspensions of MgPc (4mg in 10ml H2O) withTritonX-100, 5 mg MgPc with CTAB and 3 mg MgPc with SDBS were sonicated for 1h with and without surfactants.
This can be explained in terms of electrostatic repulsion of positive charges between the metal Pc and the surfactants destabilizing the LUMO of the MgPc nanoparticles and hence giving rise to a hypsochromic shift.
Table-1: UV-visible absorption values of MgPc bulk, solution and nano dispersed particles.
10 illustrates the effect of surfactant on the colo rof the MgPc dispersion.
As in all receding horizon predictive control strategies, the control law provides that, for each channel 'i', the control-increment [DELTA][u.sub.i](t) which minimizes the following unconstraint cost problem of the MGPC method :
Unfortunately, this algorithm is difficult to extend to the MGPC method for two reasons: the first one is due to a large dimension of the inequality constraints which needs excessive computation time.
Now, we are able to find the optimal control of the MGPC law.
Consequently, the given optimal control vector of the MGPC method cannot satisfy some specifications and also some constraints are non-satisfactoriness' in some range time.
The results are compared with those given by the MGPC method using the standard PSO algorithm.
The MGPC method is tuned by choosing: ([N.sup.i.sub.2],[N.sup.i.sub.u], [[lambda].sub.i]).sub.i=1,2] = (8,6,0.01) at time range t :=[0,400] minutes.