Two degree of freedom fractional PI scheme for automatic voltage regulation

The effectiveness of the inferential control scheme based on robust fractional-order proportional integral (FOPI) controller is presented for automatic voltage regulation (AVR) applications. The method uses two degree of freedom (2DOF) in FOPI scheme, which is tuned with the whale optimization algorithm (WOA). Actually, any AVR needs to keep the reactive power of synchronous generator at demand level, stable voltage and frequency of the electrical power supplies. In this study, the 2DOF FOPI controller is proposed to deviate away from the standard integer order, to show the superiority of extra degree of freedom in both structure and controller. To improve the AVR performance, a new performance measure is proposed for the parameter tuning. The method acquires the significant robustness in parameter perturbation and disturbance interruptions. It is observed in the step response quality that the overshoot and settling time can be reduced to approximately by half than the recently published scheme. The various analyses are shown to accept the dominance of the proposed controller in terms of robustness

PID Controller Design for Mobile Robot Using Bat Algorithm with Mutation (BAM)

By definition, a mobile robot is a type of robotthat has capability to move in a certain kind of environmentand generally used to accomplish certain tasks with somedegrees of freedom (DoF). Applications of mobile robots coverboth industrial and domestic area. It may help to reduce risk tohuman being and to the environment. Mobile robot is expectedto operate safely where it must stay away from hazards such asobstacles. Therefore, a controller needs to be designed to makethe system robust and adaptive. In this study, PID controller ischosen to control a mobile robot. PID is considered as simpleyet powerful controller for many kind of applications. Indesigning PID, user needs to set appropriate controller gain toachieve a desired performance of the control system, in termsof time response and its steady state error. Here, anoptimization algorithm called Bat Algorithm with Mutation(BAM) is proposed to optimize the value of PID controller gainfor mobile robot. This algorithm is compared with a wellknownoptimization algorithm, Particle Swarm Optimization(PSO). The result shows that BAM has better performancecompared to PSO in term of overshoot percentage and steadystate error. BAM gives 2.29% of overshoot and 2.94% ofsteady state error. Meanwhile, PSO gives 3.07% of overshootand 3.72% of steady state error

Control of Quarter-Car Active Suspension System Based on Optimized Fuzzy Linear Quadratic Regulator Control Method

Vehicle suspension systems, which affect driving performance and passenger comfort, are actively researched with the development of technology and the insufficient quality of passive suspension systems. This paper establishes the suspension model of a quarter of the car and active control is realized. The suspension model was created using the Lagrange–Euler method. LQR, fuzzy logic control (FLC), and fuzzy-LQR control algorithms were developed and applied to the suspension system for active control. The purpose of these controllers is to improve car handling and passenger comfort. Undesirable vibrations occur in passive suspension systems. These vibrations should be reduced using the proposed control methods and a robust system should be developed. To enhance the performance of the fuzzy logic control (FLC) and fuzzy-LQR control methods, the optimal values of the coefficients of the points where the feet of the member functions touch are calculated using the particle swarm optimization (PSO) algorithm. Then, the designed controllers were simulated in the computer environment. The success of the control performance of the applied methods concerning the passive suspension system was compared in percentages. The results are presented and evaluated graphically and numerically. Using the integral time-weighted absolute error (ITAE) criterion, the methods were compared with each other and with the studies in the literature. As a result, it was found that the proposed control method (fuzzy-LQR) is about 84.2% more successful in body motion, 90% in car acceleration, 84.5% in suspension deflection, and 86.7% in tire deflection compared to the studies in the literature. All these results show that the car’s ride comfort has been significantly improved

Elevation, pitch and travel axis stabilization of 3DOF helicopter with hybrid control system by GA-LQR based PID controller

This research work presents an efficient hybrid control methodology through combining the traditional proportional-integral-derivative (PID) controller and linear quadratic regulator (LQR) optimal controlher. The proposed hybrid control approach is adopted to design three degree of freedom (3DOF) stabilizing system for helicopter. The gain parameters of the classic PID controller are determined using the elements of the LQR feedback gain matrix. The dynamic behaviour of the LQR based PID controller, is modeled and the formulated in state space form to enable utlizing state feedback controller technique. The performance of the proposed LQR based LQR controller is improved by using Genetic Algorithm optimization method which are adopted to obtain optimum values for LQR controller gain parameters. The LQR-PID hybrid controller is simulated using Matlab environment and its performance is evaluated based on rise time, settling time, overshoot and steady state error parameters to validate the proposed 3DOF helicopter balancing system. Based on GA tuning approach, the simulation results suggest that the hybrid LQR-PID controller can be effectively adopted to stabilize the 3DOF helicopter system

Robust pole placement using firefly algorithm

In this paper, the new automatic tool that is based on the firefly algorithm whose purpose is optimization of pole location in the control of state feedback has been presented. The aim is satisfying specifications of performance like settling and rise time, steady state as well as overshoot error. Utilization of Firefly algorithm has demonstrated the benefits of controllers based on this kind of time domain over controllers based on the frequency domain like Proportional-Integral Derivative (PID). The presented method is more particular for the multi-input multi-output (MIMO) systems that have substantial state numbers. The simulation results indicated that the proposed method had superior performance in providing solution to the problems that involved stabilization of helicopter under the Rationalized Model of helicopter/ Moreover, it demonstrates the Firefly algorithm effectiveness with regards to, the state observer design and feedback controller and auto-tuning

Selfish Herd Optimisation based fractional order cascaded controllers for AGC study

In a modern, and complex power system (PS), robust controller is obligatory to regulate the frequency under uncertain load/parameter change of the system. In addition to this, presence of nonlinearities, load frequency control (LFC) of a Power System becomes more challenging which necessitates a suitable, and robust controller. Single stage controller does not perform immensely against aforesaid changed conditions. So, a novel non-integer/fractional order (FO) based two-stage controller incorporated with 2-degrees of freedom (2-DOF), derivative filter (N), named as 2-DOF-FOPIDN-FOPDN controller, is adopted to improve the dynamic performance of a 3-area power system. Each area of the power system consists of both non-renewable and renewable generating units. Again, to support the superior performance of 2-DOF-FOPIDN-FOPDN controller, it is compared with the result produced by PID, FOPID, and 2-DOF-PIDN-PDN controllers. The optimal design of these controllers is done by applying Selfish Herd Optimisation (SHO) technique. Further, the robustness of the 2-DOF-FOPIDN-FOPDN controller is authenticated by evaluating the system performance under parameter variation. The work is further extended to prove the supremacy of SHO algorithm over a recently published article based on pathfinder algorithm (PFA)

Design of PID, FLC and Sliding Mode Controller for 2-DOF Robotic Manipulator: A Comparative Study

Controlling the manipulators in a precise manner is a challenging task. To overcome this difficulty around the world, many researchers have developed various control algorithms but are not providing optimal results. To obtain the optimal results in the current research the authors designed a proportional, integral, and derivative (PID) controller, fuzzy logic controller (FLC), and sliding mode controller (SMC) for a 2-DOF manipulator. The concept of forward and inverse kinematics was initially solved after assigning the D-H parameters for each joint. The purpose of forward or direct kinematics is to obtain the position and orientation of the end effector. Further, the concept of inverse kinematics is used to estimate the joint angles. Later on, the Lagrange-Euler formulation was used to calculate the dynamics of the 2-DOF manipulator, which is required to estimate the torque required for each joint of the robotics arm. The main goal of this research problem is to optimize the angular error between the two successive events. Finally, the developed algorithm is compared with the existing algorithms such as PID and Fuzzy logic controller

Observer Sliding Mode Control Design for lower Exoskeleton system: Rehabilitation Case

Sliding mode (SM) has been selected as the controlling technique, and the state observer (SO) design is used as a component of active disturbance rejection control (ADRC) to reduce the knee position trajectory for therapeutic purposes. The suggested controller will improve the needed position performances for the Exoskeleton system when compared to the proportional-derivative controller (PD) and SMC as feed-forward in the ADRC approach, as shown theoretically and through computer simulations. Simulink tool is used in this comparison to analyze the nominal case and several disruption cases. The results of mathematical modeling and simulation studies demonstrated that SMC with a disturbance observer strategy performs better than the PD control system and SMC in feed-forward with a greater capacity to reject disturbances and significantly better than these controllers. Performance indices are used for numerical comparison to demonstrate the superiority of these controllers

Decoupled integral lqr controller with anti-windup compensator for MIMO two rotor aerodynamical system (TRAS)

This paper employs a design of two sub-controllers based on a Linear Quadratic Regulator (LQR) for Two Rotor Aero-dynamical System (TRAS) in two Degree of Freedom (2-DOF) motion. TRAS is a nonlinear Multi-Input Multi-Output (MIMO) system that resembles the behaviour of a helicopter in certain aspects. The main focus of the research work is to control and stabilize the TRAS system in 2-DOF so that the desired trajectory is tracked quickly and accurately even in the presence of disturbances. However, this not always possible due to some reasons such as the strong cross couplings, poorly tuned control parameters and integral windup phenomena that significantly deteriorate the transient response. In this work, TRAS is decoupled into two subsystems (horizontal and vertical) with the cross couplings considered as disturbances. The derivation of the linear model of each subsystem is developed using Jacobean linearisation matrix. An optimal LQR controller is designed and tuned using Particle Swarm Optimisation (PSO) algorithm for each subsystem. To get full state information, provide asymptotic tracking for the reference signal and alleviate integral windup phenomena each sub-LQR controller has been combined with full state observer, integral action gain and anti-windup compensator based on back-calculation technique, respectively to ensure fast and reliable control of TRAS system without degrading the transient response. Experimental results show that the Decoupled Integral LQR Controller (DILQRC) exhibits a better performance in terms of transient and steady state responses with significant reduction of settling time, overshoot percentage and error index it also produces less aggressive and smooth control signals as compared to the Cross Coupled PID Controller (CCPIDC) tuned by the manufacturer

Fractional Order Fuzzy Control of Hybrid Power System with Renewable Generation Using Chaotic PSO

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.This paper investigates the operation of a hybrid power system through a novel fuzzy control scheme. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, aqua electrolyzer etc. Other energy storage devices like the battery, flywheel and ultra-capacitor are also present in the network. A novel fractional order (FO) fuzzy control scheme is employed and its parameters are tuned with a particle swarm optimization (PSO) algorithm augmented with two chaotic maps for achieving an improved performance. This FO fuzzy controller shows better performance over the classical PID, and the integer order fuzzy PID controller in both linear and nonlinear operating regimes. The FO fuzzy controller also shows stronger robustness properties against system parameter variation and rate constraint nonlinearity, than that with the other controller structures. The robustness is a highly desirable property in such a scenario since many components of the hybrid power system may be switched on/off or may run at lower/higher power output, at different time instants