pid control of 2nd order mass force system labview

Compared to the heuristic PID tuning method of Ziegler-Nichols, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error rise time, settling time and maximum overshoot in speed control of DC motor.Īn analytical method for PID controller tuning with specified gain and phase margins for integral plus time delay processes. Simulation results are presented to show that the PSO-Based optimized PID controller is capable of providing an improved closed-loop performance over the Ziegler- Nichols tuned PID controller Parameters. Ziegler- Nichols, tuning method was applied in the PID tuning and results were compared with the PSO-Based PID for optimum control. This approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency over the conventional methods. This paper presents an artificial intelligence (AI method of particle swarm optimization (PSO algorithm for tuning the optimal proportional-integral derivative ( PID controller parameters for industrial processes. This tuning which is application specific also deteriorates with time as a result of plant parameter changes. However, manual tuning of these controllers is time consuming, tedious and generally lead to poor performance. Proportionalâ€“Integralâ€“ Derivative ( PID Controller Tuning using Particle Swarm Optimization Algorithmĭirectory of Open Access Journals (Sweden)įull Text Available The proportional-integral-derivative ( PID controllers are the most popular controllers used in industry because of their remarkable effectiveness, simplicity of implementation and broad applicability. The proposed self tuning fuzzy PID type controller has been compared with the fuzzy PID type controller without a self tuning mechanism and the conventional integral controller through some performance indices A two area interconnected system is assumed for demonstrations. The self tuning mechanism depends on the peak observer idea, and this idea is modified and adapted to the LFC problem. Moreover, there exists a self tuning mechanism that adjusts the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral coefficient of the PID type fuzzy logic controller in an on-line manner. The fuzzy PID type controller is constructed as a set of control rules, and the control signal is directly deduced from the knowledge base and the fuzzy inference. In this paper, a self tuning fuzzy PID type controller is proposed for solving the load frequency control (LFC) problem. International Nuclear Information System (INIS) Self tuning fuzzy PID type load and frequency controller

Pid control of 2nd order mass force system labview