The Smith method has been used to control physical plants with dead time components, where plant states after the dead time is elapsed are predicted and a control input is determined based on the predicted states. We extend the method to the symbolic control and design a symbolic Smith controller to deal with a nondeterministic embedded system. Due to the nondeterministic transitions, the proposed controller computes all reachable plant states after the dead time is elapsed and determines a control input that is suitable for all of them in terms of a given control specification. The essence of the Smith method is that the effects of the dead time are suppressed by the prediction, however, which is not always guaranteed for nondeterministic systems because there may exist no control input that is suitable for all predicted states. Thus, in this paper, we discuss the existence of a deadlock-free symbolic Smith controller. If it exists, it is guaranteed that the effects of the dead time can be suppressed and that the controller can always issue the control input for any reachable state of the plant. If it does not exist, it is proved that the deviation from the control specification is essentially inevitable.

This paper presents a parallelization method utilizing dead time to implement higher precision feedback control systems in multicore processors. The feedback control system is known to be difficult to parallelize, and it is difficult to deal with the dead time in control systems. In our method, the dead time is explicitly represented as delay elements. Then, these delay elements are distributed to the overall systems with equivalent transformation so that the system can be simulated or executed in parallel pipeline operation. In addition, we introduce a method of delay-element addition for parallelization. For a spring-mass-damper model with a dead time, parallel execution of the model using our technique achieves 3.4 times performance acceleration compared with its sequential execution on an ideal four-core simulation and 1.8 times on a cycle-accurate simulator of a four-core embedded processor as a threaded application on a real-time operating system.

This paper deals with new fuzzy controller for handling systems having large dead time and nonlinearities, via approximations of large rule fuzzy logic controller by simplest fuzzy controller (4 rules). The error between large rule fuzzy controller and simplest fuzzy controller are compensated by proposed compensating factors. These compensating factors are modified to handle large dead time and nonlinear systems. Features of proposed approximations are discussed. The concept of variation of nonlinearity factor of fuzzy controller is also discussed. Various processes from different literatures are utilized to demonstrate the proposed methodology. After doing many simulations it has been found that with proper tuning, overall system handles large dead time and nonlinearity which may be difficult by conventional methods. The processes are also simulated for load disturbances and change of operating point (set point) and it has been found that proposed scheme is robust for long dead times.