The aim of this research is to design a PID Controller using particle swarm optimization (PSO) algorithm for multiple-input multiple output (MIMO) Takagi-Sugeno fuzzy model. The conventional gain tuning of PID controller (such as Ziegler-Nichols (ZN) method) usually produces a big overshoot, and therefore modern heuristics approach such as PSO are employed to enhance the capability of tradition...

This paper demonstrates the implementation of PID controller tuning using evolutionary technique which is Genetic Algorithm (GA). The optimal PID control scheme is applied to higher order system. The execution of this evolutionary strategy is evaluated by setting the objective function as mean square error (MSE), Integral time absolute error (ITAE) and Integral absolute error (IAE) one at a tim...

In this paper we propose a method for optimization of closed-loop parameters and continuous-time sampling period by digital self-tuning PID control of pressure plant. The quality of pressure plant control is experimentally compared between two modifications of digital self-tuning PID controllers. The results of adaptive pressure plant control show that the optimization of closed-loop parameters...

This paper presents an implementation of self-tuned PID controller (FPID) for speed control of DC motor based on LabVIEW (Laboratory Virtual Instrument Engineering Workbench Environment). The algorithms of fuzzy PID controller (FPID) and conventional PID controller (CPID) are implemented using PID and Fuzzy Logic simulation toolkits of the Lab View environment. The simulation results demonstrat...

A new method for PID controller tuning based on process models for cascaded control systems is proposed in this paper. The method consists of first finding the ideal controller that gives the desired closed loop response and then finding the PID approximation of the ideal controller by Maclaurin series. This method can be applied to any open loop stable processes. Furthermore, it enables us to ...

Abstract— The aim of this paper is to study the tuning of a PID controller using swarm optimization techniques. In this paper, comparative performance of PSO and BF-PSO based PID controller is analyzed. PSO algorithm converges rapidly during the initial stages of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance t...

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling techn...

In this paper, a new improved Differential Search Algorithm optimization approach is proposed and successfully applied to the design and tuning of a PID-type Fuzzy Logic Controller. The scaling factors tuning problem of the Fuzzy Logic Controller structure is formulated and systematically resolved, using the improved constrained Differential Search Algorithm-based method. A comparison, with the...

This paper illustrates the benefits of a self-tuning PID strategy applied to a proton exchange membrane fuel cell system. Controller parameters are updated on-line, at each sampling time, based on an instantaneous linearization of an artificial neural network model of the process and a General Minimum Variance control law. The self-tuning PID scheme allows managing nonlinear behaviors of the sy...

PID controllers are designed and optimized in this paper for wood-berry distillation column using simulated annealing algorithm and particle swarm optimization method. PID controllers are the common instruments used in control applications. Construction of PID controllers is smooth and easy. It furnishes more stability and malleable while governing the processes. Thousands of PID loops strive t...