It is usual that we are able to describe the control strategy in natural language. Our approach enables using natural language directly without thinking of the way how is the proper fuzzy control realized. Thus, the user should not think of shapes of fuzzy sets, used operations, inference engine, etc., as it is otherwise usual in fuzzy control widely considered elsewhere. We speak about linguistically oriented fuzzy control and the corresponding system is called Linguistic Fuzzy Logic Controller (LFLC). We may also see LFLC as if “partner” whose task is to realize control according to instruction given in natural language. Note that such situation is not so unusual; remember, e.g., instruction given by teacher in cardriving school.
Using the software systems LFLCSim and LFLC2000 we developed several tens of simulations of control of various kinds of processes. The fuzzy PI, PD, and PID controllers have been implemented in them. A real application of linguistically oriented fuzzy control is described in [1].
Simple PI control
FControlOP12.swf
Similar demonstration shows control of inverted pendulum.
FControlPendulum.swf
Universal PI control
There exists general linguistic description for PI fuzzy control of wide range of processes.
No.  E  dE  dU  No.  E  dE  dU 
1.  Ze  Ze  Ze  19.  Me  +Sm  ExSm 
2.  +Bi  +NoZe  +Bi  20.  +Sm  +NoSm  +Me 
3.  Bi  NoZe  Bi  21.  Sm  NoSm  Me 
4.  +Bi  NoSm  Ze  22.  +Sm  NoSm  VeSm 
5.  Bi  +NoSm  Ze  23.  Sm  +NoSm  +VeSm 
6.  +Bi  RoZe  +Me  24.  +Sm  RoZe  +VeSm 
7.  Bi  RoZe  Me  25.  Sm  RoZe  VeSm 
8.  +Bi  Sm  +Me  26.  +Sm  +Sm  +Sm 
9.  Bi  +Sm  Me  27.  +Sm  Sm  +ExSm 
10.  +Me  +NoSm  +Bi  28.  Sm  +Sm  ExSm 
11.  Me  NoSm  Bi  29.  Sm  Sm  Sm 
12.  +Me  NoSm  VeSm  30.  +VeSm  Sm  Sm 
13.  Me  +NoSm  +VeSm  31.  VeSm  +Sm  +Sm 
14.  +Me  RoZe  +Me  32.  +VeSm  VeSm  Ze 
15.  Me  RoZe  Me  33.  VeSm  +VeSm  Ze 
16.  +Me  +Sm  +Me  34.  RoZe  +VeSm  +ExSm 
17.  Me  Sm  Me  35.  RoZe  VeSm  ExSm 
18.  +Me  Sm  +ExSm 




The following set of demonstrations shows the use of this linguistic description in the control of 6 different processes. The description is in all cases the same, only linguistic context (scaling) of the variables had to be set.
FControlPIDipl1.swf
FControlPIDipl2.swf
FControlPIDipl3.swf
FControlPIDipl4.swf
FControlPIDipl5.swf
FControlPIDiplUnstable.swf
Learning fuzzy control
REFERENCES:
[1] NOVÁK, V. Foundations of fuzzy modeling (Základy fuzzy modelování). Praha: BENtechnická literatura, 2000. 166 pp. ISBN 8073000091 (in Czech).
Plenary talk at 15th Carpathian International Control Conference, Velke Karlovice, Czech Republic 2014.Magnetic levitation using PID controller
Magnetic levitation using LFLC Controller