Traditional Integer Order PID Controller Research Articles

A hybrid SCSO-QNN approach based load frequency control of three area power system with renewable sources using FOPID controller

ABSTRACT This research proposes a hybrid SCSO-QNN method for designing a FOPID controller in a three-area power system to regulate load frequency. The proposed hybrid approach combines quantum neural networks with sand cat swarm optimization, and it is commonly named as the SCSO-QNN method. The proposed method’s primary goal is to overcome load disturbances and attain the intended output of the interconnected system. The SCSO generates controller parameters tuned by the FOPID controller, providing a significant improvement in performance, while the QNN is employed to forecast the optimal control signal of the converter. Reducing steady-state errors and improving system stability are areas where the FOPID performs better than a traditional integer-order PID controller. Moreover, SCSO-QNN optimization technique exhibits excellent convergence properties, resulting in improved control performance. The proposed method ensures system frequency control by controlling frequency deviation and power fluctuations in the connect line during load disturbances. The proposed method is executed on the MATLAB platform and contrasted with current techniques. The proposed technique outperforms all current techniques, including ABC-FOPID, Genetic Algorithm, and Artificial Bee Colony PID. The proposed method Area control error is 1.8%, which is less than other existing methods.

Auto-Tuning Parameters of Fractional PID Controller Design for Air-Conditioning Fan Coil Unit

The traditional integer order PID controller manipulates the air-conditioning fan coil unit (FCU) that offers cooling and heating loads to each air-conditioning room in summer and winter, respectively. In order to maintain a steady indoor temperature in summer and winter, the control quality cannot meet the related requirements of air-conditioning automation, such as large overshoot, large steady state error, long regulating time, etc. In view of these factors, this paper develops a fractional order PID controller to deal with such problem associated with FCU. Then, by varying mutation factor and crossover rate of basic differential evolution algorithm adaptively, a modified differential evolution algorithm (MDEA) is designed to tune the satisfactory values of five parameters of indoor temperature fractional order PID controller. This fractional order PID control system is configured and the corresponding numerical simulation is conducted by means of MATLAB software. The results indicate that the proposed fractional order PID control system and MDEA are reliable and the related control performance indexes meet with the related requirements of comfortable air-conditioning design and control criteria.

Fractional-order PID controller for permanent magnet DC motor based on PSO algorithm

<span>This paper proposes the fractional-order proportional integral derivative (FOPID) controller, as a speed controller for permanent magnet direct current (PMDC) motor, instead of the traditional integer-order PID controller. The FOPID controller is the general form of the integer-order PID controllers, which found wide applications in all engineering fields. In this work a hybrid M-file and SIMULINK program is developed to simulate the overall system, the FOPID controller has five associated parameters. The optimum values of those parameters are found out by using particle swarm optimization technique. Simulation results show excellent command speeds tracking and superior dynamic response in conjunction with that of the integer-order PID controller. The proposed controller shows a high ability to overcome any external disturbance the system may be exposed; also, it performs a high degree of robustness to control the system in motoring and regenerative operating modes.</span>

Fractional order PIλDμ controller design for satisfying time and frequency domain specifications simultaneously

In order to achieve a desired control performance characterized by satisfying specifications in both frequency-domain and time-domain simultaneously, an optimal fractional order proportional integral derivative (PIλDμ) controller design strategy is proposed based on analytical calculation and Differential Evolution algorithm for a permanent magnet synchronous motor (PMSM) servo system in this paper. In this controller design, the frequency-domain specifications can guarantee the system stability with both gain margin and phase margin, and also the system robustness to loop gain variations. The time-domain specifications can ensure the desired step response performance with rapid rising curve, constrained overshoot, and proper power consuming. Compared with the PIλ controller and the traditional PID controller, PIλDμ controller can get obvious benefits from two more degrees of freedom of the fractional orders λ and μ on satisfying multiple constraints simultaneously and achieving better servo tracking performance for the PMSM servo system. PMSM speed tracking simulations and experiments are demonstrated to show the significant advantages of using the proposed optimal PIλDμ controller over the optimal fractional order PIλ controller and traditional integer order PID controller.

Optimization design on fractional order PID controller based on adaptive particle swarm optimization algorithm

Compared with traditional integer-order PID controller, fractional order PID controller can expand the range of its parameters and control controlled objects more flexibly. It has become one of the research focuses in control field in recent years. Directing at the problem that it is not easy for model parameters of nonlinear fractional order PID controller to be determined, this paper presents a new adaptive particle swarm optimization algorithm which is named YLPSO and can conduct automatic setting of parameters for fractional order PID controller. This algorithm, mainly adopting strategies of adaptive dynamic weight and asynchronization adjustment of learning factors, realizes ability in intensifying algorithm convergence to global optimum by balancing global searching performance and local searching performance of PSO algorithm. Simulation results show that, compared with differential evolution algorithm and standard particle swarm optimization algorithm, YLPSO can control parameter optimizing effect better. Algorithm put forward in this paper provides a new reference for combination of intelligent optimization algorithm and nonlinear fractional order controller.

Fractional Order PID Control of Railway Rescue Crane Leveling System

Aiming at the overshoot problem of electro-hydraulic position servo system used in the process of railway rescue crane hydraulic automatic leveling, and based on its characteristics such as big output power, high control accuracy, quick response speed, et al, this paper established the linear mathematical model of railway rescue crane electro-hydraulic automatic leveling system, besides, the fractional order PID control method was proposed based on the oustaloup digital filter algorithm and the working principle of fractional order PID control method was given, and then the fractional order PID controller was designed. In order to verify the effectiveness of the proposed control strategy, the MATLAB/Simulink simulation software was used. The simulation results show that the fractional order PID controller improved the speed of electro-hydraulic servo system unit step response and the capacity of resisting disturbance compared to traditional integer order PID controller, besides it can ensure the response without overshoot at the same time, so it meets the requirements for rapidity and no overshoot of railway rescue crane hydraulic automatic leveling system very well.

The Frequency Research of Fractional Order PIλDμ Controller

Since most of the control systems in real industrial production are fractional，there is necessery to propose fractional order PIλDμ controller, which extend the traditional integer-order PID controller to fractional order, it has increased two free degree: Integral-order λ and differential-order μ, to more accurately control those complex systems. At the same time analysis the performance of fractional order PIλDμ controller in frequency domain. Especially,the two degrees’ effect to controller.