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This paper aims to describe Metamodeling approach, a technique that can be utilized to tune controller parameters for a non-linear process quickly, and how it is used to solve real world engineering problems by applying it to the problem of designing a proportional-integral-derivative (PID) controller. The process used in this study is a single input single output (SISO) evaporator system which is...
This paper aims at the Genetic Algorithm (GA's) based tuning of fuzzy logic controller (FLC). A two-step approach is proposed to tune a fuzzy logic controller using genetic algorithm. Moreover, it has been tried to develop a stepwise method to tune a fuzzy logic controller with GA in less number of generations. Special attention has been given to the learning of knowledge base which can be used for...
This paper proposes a new tuning method for PI controllers in two-degree-of-freedom (2DOF) structure. In design approach, first order plus dead time (FOPDT) model is used. The aim is to have good set-point response and disturbance rejection and also maximum robustness to model uncertainties. The tuning strategy is based on using Butterworth rules and genetic algorithm optimization. Simulation results...
The design of fuzzy logic controllers involves the rationalization of the Fuzzy Inferencing Rules and the appropriate selection of the input and output membership functions. This typically have been achieved by the application of expert knowledge of plant operation and by the appropriate selection of weighting gains. This paper presents the fuzzy logic controller with certain parameters which can...
In the main frame of the optimal control process has to be focused this work, where a methodology based on the performance of Genetic Algorithms to be used to search the appropriate knowledge base, defined in the sense of Fuzzy Logic, for the process controller. Two stages have to be considered to obtain the control system - Initial Stage and Conclusions Phase. First point search the control law for...
A method to design simple linear controllers for mildly nonlinear systems is presented. In order to design the desired controller we approximate the behavior of the nonlinear system with a set of linear systems which are derived through linearizations. Classical local linearization is carried out around stationary points but in order to have a better approximation of the nonlinear system selected...
The quality of an intelligent control system is the ability to control the process with a certain degree of autonomy. These requirements, as an autonomous process controller are ever increasing. Considering the fact that existing algorithm based controllers such as the adaptive PID have their own limitations/are inadequate, the controllers are designed to emulate human mental faculties such as adaptation,...
Differential evolution is a high-performance optimizer that is very easy to understand and implement. It is similar in some ways to genetic algorithms or evolutionary algorithms, but requires less computational bookkeeping and generally only a few lines of code. In this paper, a differential evolution optimizer is implemented and compared to a particle swarm optimization for control of a first-order...
The translational oscillations with a rotational proof-mass actuator (TORA) is a well-known benchmark for examining the advantages and limitations of different nonlinear control design techniques. In this paper, a single-input-rule-modules (SIRMs) based type-2 fuzzy logic control scheme is proposed for this nonlinear multivariable system. And, genetic algorithms (GAs) are adopted to determine the...
According to seriously nonlinear, time - varying and strong coupling of the temperature and humidity of drying process, the immune feedback mechanism and fuzzy control theory were applied to designing a fuzzy immune PID controller, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control...
This paper presents a method of designing proportional-integral-derivative (PID) controller based on genetic algorithms (GA). Ziegler-Nichols tuning formula has been used for predicting the range of gain coefficients of GA-PID controller. The use of GA for optimizing the gain coefficients of PID controller has considerably improved the performance of PID controller. Simulation studies on a second-order...
Hydroelectric generating unit system of water plant is a non-linear and complicated system. Conventional controller cannot get good controlling performance in control. In this study, an advanced soft computing technique based on fuzzy, neural network and genetic algorithm is used in the control of hydroelectric generating unit system of hydropower plant. Fuzzy reasoning system is used as controller...
FRIT (fictitious reference iterative tuning) is attractive in the field of the control system design. Especially, the FRIT has some useful features in practical use. One is that it dose not require the system identification. Another is that the control parameters can be directly computed using only the closed-loop input/output data and the desired output signal. In this paper, the FRIT is extended...
An integrated flight control system is designed according to the six DOF nonlinear model of pitching channel of hypersonic vehicle X-43A. The system is composed of one fuzzy controller and two PD controllers. Based on genetic algorithm, the optimization process of fuzzy control rules and PD feedback parameters is carried out automatically without expertspsila knowledge and training data in advance...
Considering the pitching channel of air breathing hypersonic vehicle X-43A as plant, flight control system was designed according to the 6 degree of freedom nonlinear model. The flight control system includes two loops, of which the structure is conventional mode. The guidance loop is a PD controller, while the control loop is composed of two fuzzy logic controllers. The guidance loop leads the vehicle...
The work described in his paper aims at exploring the use of soft computing techniques for designing a controller to perform control of level in a spherical tank. First, system identification of this nonlinear process is done using black box model, which is identified to be non linear and approximated to be a first order plus dead time (FOPDT) model. Then the controller tuning strategy has been applied...
Often it is difficult to acquire the requisite knowledge in the design of rule-based control systems. In the study, an advanced knowledge acquisition technique is presented and used in the fuzzy control of hydroelectric generating unit system of hydropower plant. Genetic algorithm is employed to optimize the parameters and rules of fuzzy controller in design controller and real-time control process...
There are many complex industrial processes with highly nonlinear and uncertain characteristics which are generally difficult to control by well known PID controllers. Active disturbance rejection control (ADRC), a relatively recent nonlinear control method, is an alternative framework which has the advantages on simple algorithm, strong robustness, and less dependence on the mathematical models of...
In this paper, an improvement of sliding mode control design is investigated. A fast reaching velocity into the switching hyperplane in the hitting phase and little chattering phenomena in the sliding phase is desired. A fuzzy sliding mode control (FSMC) in cooperation with genetic algorithms (GAs) in coupled tanks problem is studied. A fuzzy logic controller is used to replace the discontinuity in...
An approach is proposed which improves the quality and speed of manual loop shaping. Loop shaping is an iterative and creative controller design procedure where the control engineer uses frequency response function (FRF) data of the plant to shape the open loop response such that it satisfies stability, performance and robustness specifications. The advantage compared to automated controller design...
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