many real time processes have complex, uncertain and nonlinear dynamics. boilers are nonlinear, time varying, multi-input multi-output (mimo) systems, whose states generally vary with operating conditions. the major problem in controlling that system is that its drum water pressure and steam flow dynamics include an integrator that results a critically stable behavior. conventional controller p...

This paper proposes a novel controller design method based on using artificial bee colony (ABC) algorithms for an unstable nonlinear continuously stirred tank reactor (CSTR) chemical system. Such CSTR process is highly nonlinear and its dynamic is significantly dominated by system parameters. It is a good challenge to access the controller design performance when the controller is applied in th...

This paper presents a comparative study of different control design methods applied to a nuclear reactor model. A nuclear reactor temperature controller is designed using the H-infinity (H∞) control. This advanced controller is compared with a conventional Proportional–Integral–Derivative controller (PID) controller and a traditional optimal controller design using Linear Quadratic Gaussian (LQ...

The intelligent control technology with the traditional control theory formats intelligent compound controller in order to learn from each other and improve the overall advantage of complementary features. Fuzzy PID control neuron PID control, fuzzy sliding mode control, and optimal control of the neural network. This paper discusses the current situation and development of smart composite cont...

A robust control scheme is proposed for the position control of the electrohydrostatic actuator (EHA) when considering hardware saturation, load disturbance, and lumped system uncertainties and nonlinearities. To reduce overshoot due to a saturation of electric motor and to realize robustness against load disturbance and lumped system uncertainties such as varying parameters and modeling error,...

Nowadays, there are a lot of different control methodologies that could be used within industrial processes. Some of these methodologies have a complex design and also demands an extra engineering effort to design the controller with a superior performance. Some other controllers may not lead to a desirable performance although they are too easy to design. The most common controller used on che...

In this paper a novel Optimal Type-2 Fuzzy Proportional-Integral-Derivative Controller (OT2FPIDC) is designed for controlling the air supply pressure of Heating, Ventilation and Air-Conditioning (HVAC) system. The parameters of input and output membership functions, and PID controller coefficients are optimized simultaneously by random inertia weight Particle Swarm Optimization (RNW-PSO). Simul...

In this paper, a robust controller design method is first formulated to deal with both performance and robust stability specifications for multivariable processes. The optimum problem is then dealt with using a loop-shaping H∞ approach, which gives a sub-optimal solution. Then a PID approximation method is proposed to reduce a high-order controller. The whole procedure involves selecting severa...

This paper is concerned with the design of Multi-Inputs and Multi-Outputs (MIMO) predictive PID controllers, which have similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the MIMO PID gains are calculated using th...

This paper presents the implementation of PID controller tuning using two sets of evolutionary techniques which are differential evolution (DE) and genetic algorithm (GA). The optimal PID control parameters are applied for a high order system, system with time delay and non-minimum phase system. The performance of the two techniques is evaluated by setting its objective function with mean squar...