Design of fractional order PID controller for automatic regulator voltage system based on multi-objective extremal optimization

Fractional order PID (FOPID) controllers are introduced as a general form of classical PID controllers using fractional calculus. As this controller provides good disturbance rejection and is robust against plant uncertainties it is appropriate for the vibration mitigation in structures. In this paper, an FOPID controller is designed to adjust the contact force of piezoelectric friction dampers for semi-active control of base-isolated structures during far-field and near-field earthquake excitations. A multi-objective cuckoo search algorithm is employed to tune the controller parameters. Considering the resulting Pareto optimal front, the best input for the FOPID controller is selected. For seven pairs of earthquakes and nine performance indices, the performance of the proposed controller is compared with those provided by several well-known control techniques. According to the simulation results, the proposed controller performs better than other controllers in terms of simultaneous reduction of the maximum base displacement and story acceleration for various types of earthquakes. Also, it provides acceptable responses in terms of inter-story drifts, root mean square of base displacements and floor acceleration. In addition, the evaluation of robustness for a stiffness uncertainty of ±10% indicates that the proposed controller gives a robust performance against such modeling errors.

Fractional order PID control design for semi-active control of smart base-isolated structures: A multi-objective cuckoo search approach.

Considering the higher flexibility in tuning process and finer control action of the fractional-order proportional integral derivative (FOPID) controller over the conventional proportional integral derivative (PID) controller, this paper explores its application in the automatic voltage regulator system. FOPID contains five tuning parameters as compared to three in the conventional PID controller. The additional tuning knobs in FOPID provide increased control flexibility and precise control action, however, their inclusion makes the tuning process more complex and tedious. Thus, the intelligence of an artificial intelligence (AI) technique called jaya optimization algorithm (JOA) is utilized in order to obtain an optimal combination of FOPID gains which further led to the optimal transient response and improved stability of the considered AVR system. To validate the performance superiority of the proposed approach its corresponding system’s dynamic response is compared with that of the other well-known AI-based approaches explored in recent literature. Furthermore, the stability study of the proposed AVR system is carried out by evaluating its pole/zero and bode maps. Finally, the robustness of the proposed optimized AVR system against the system’s parameter variation is evaluated by varying the time constants of all the four components of AVR (generator, exciter, amplifier and sensor) from −50% to +50% independently. The proposed algorithm based FOPID tuning technique provides 59.82%, 56.09%, 14.94%, 34.24%, 35.70%, 21.64%, 12.0%, 41.33%, 14.84% and 15.17% reduced overshoot than that of differential evolution (DE), particle swarm optimization (PSO), Artificial Bee Colony (ABC), Bibliography Based Optimization (BBO), Grasshopper Optimization Algorithm (GOA), Pattern Search Algorithm (PSA), Improved Kidney Inspired Algorithm (IKA), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA) and Local Unimodal Sampling (LUS) algorithm respectively, thus validates its competence and effectiveness.

Jaya optimization algorithm for transient response and stability enhancement of a fractional-order PID based automatic voltage regulator system

Owing to the superior transient and steady-state performance of the fractional-order proportional-integral-derivative (FOPID) controller over its conventional counterpart, this paper exploited its application in an automatic voltage regulator (AVR) system. Since the FOPID controller contains two more control parameters (µ and λ ) as compared to the conventional PID controller, its tuning process was comparatively more complex. Thus, the intelligence of one of the most recently developed metaheuristic algorithms, called the salp swarm optimization algorithm (SSA), was utilized to select the optimized parameters of the FOPID controller in order to achieve the optimal dynamic response and enhanced stability of the studied AVR system. To validate the effectiveness of the proposed method, its performance was compared with that of the recently used tuning methods for the same system configuration and operating conditions. Furthermore, a stability analysis was carried out using pole-zero and bode stability criteria. Finally, in order to check the robustness of the developed system against the system parameter variations, a robustness analysis of the developed system was undertaken. The results show that the proposed SSA-based FOPID tuning method for the AVR system outperformed its conventional counterparts in terms of dynamic response and stability measures.

Salp Swarm Optimization Algorithm-Based Fractional Order PID Controller for Dynamic Response and Stability Enhancement of an Automatic Voltage Regulator System

In this paper, a fractional-order model of pneumatic servo system is introduced by replacing the integer-order dynamic equation with the corresponding fractional order one. Then, a fractional-order proportional-integer-differential (FPID) controller is optimized for the servo system using an online multivariable multiobjective genetic algorithm (MMGA). The proposed MMGA searches in five-dimensional parameter space based on Pareto rank to balance multiobjectives. In order to provide a basis for comparison, the parameters of a integer order proportional-integer-differential (IPID) controller are also optimized using the same method. The performance indices defined for comparison are the steady-state tracking accuracy and the control energy consumption. Additionally, seven other methods from the literature are compared. The experimental results obtained show that the optimized FPID controller results in a better performance than the optimized IPID controller and the other existing approaches.

Optimal Design of a Fractional-Order Proportional-Integer-Differential Controller for a Pneumatic Position Servo System

In practical applications, the pure derivative action is never used, due to the “derivative kick” produced in the control signal for a step input, and to the undesirable noise amplification. It is usually replaced by a first-order low-pass filter. In this paper, we use a $$\mu $$
 -order fractional low-pass filter and define a practical fractional-order controller. The proposed approach with new defined fitness function has very easy implementation and the most control performance. We present a method for optimum tuning of practical fractional PID controllers for automatic voltage regulator system using particle swarm optimization (PSO) algorithm. PSO is a robust stochastic optimization technique based on the movement and intelligence of swarm, applies the concept of social interaction to problem solving. From the comparison this technique with the other methods, its influence and efficiency are illustrated. Simulations and comparisons with other FOPID/PID controllers illustrate that the proposed PSO-FOPID controller can provide good control performance with respect to reference input and also improve the system robustness with respect to model uncertainties.

Design of Optimal Fractional-Order PID Controllers Using Particle Swarm Optimization Algorithm for Automatic Voltage Regulator (AVR) System

This paper presents a method for optimum tuning of Fractional PID controllers using PSO algorithm which have fractional or integer order transfer functions. Particle swarm optimization (PSO) is a robust stochastic optimization technique based on the movement and intelligence of swarm, applies the concept of social interaction to problem solving. The best parameters of Fractional-Order PID controller consist of proportional gain integral gain , fractional-order of integrator λ , derivative gain and fractional-order of differentiator μ can be determinate by using this technique. The proposed approach with defined cost function has a very easy implementation and ability of fast tuning of optimum fractional-order PID controllers parameters. From the comparison this technique with the other methods, its influence and efficiency are illustrated.

Hadi Ramezanian

Papers

Design of Optimal Fractional-Order PID Controllers Using Particle Swarm Optimization Algorithm for Automatic Voltage Regulator (AVR) System

Optimal Design a Fractional-Order PID Controller using Particle Swarm Optimization Algorithm