PID and PID-like controller design by pole assignment within D-stable regions

This paper presents a new PID and PID-like controller design method that permits the designer to control the desired dynamic performance of a closed-loop system by first specifying a set of desired D-stable regions in the complex plane and then running a numerical optimisation algorithm to find the controller parameters such that all the roots of the closed-loop system are within the specified regions. This method can be used for stable and unstable plants with high order degree, for plants with time delay, for controller with more than three design parameters, and for various controller configurations. It also allows a unified treatment of the controller design for both continuous and discrete systems. Examples and comparative simulation results are pro-vided to illustrate its merit

An Application of Symmetrical Optimum Method to Servo Systems with Variable Inertia

The paper presents an application of the Symmetrical Optimum method under the form of the Extended Symmetrical Optimum method to the design of controllers for servo systems with variable inertia. A brushless direct current servo system with variable inertia is considered as the plant. A proportional-integral controller is tuned for the speed control of this plant using the Extended Symmetrical Optimum method. The results are shown for four values of the moment of inertia and two variable reference input shapes

Azadi Controller Influentially Succeeds in the Eminent Plant Automations

667-670This paper is devoted to present Azadi controller, which is based on a positive feedback surrounded with two negative feedbacks. This controller performs influential over the classical optimum PID controllers. Classical PID controllers have been extensively applied to the linear or nonlinear systems for many years. There are many approaches to tune these PID controllers. Among those, are Zigler-Nicols (ZN), Chien-Hrones-Reswick (CHR), Cohen–Coon (CC), and some optimum controllers such as Modulus Optimum (MO), Symmetrical Optimum (SO). However, when the plant has larger delays, Smith predictor (SP) becomes a good candidate to overcome the plant oscillations. Azadi controller actually is an adaptive controller which performs much better than those optimum classical controllers from many control features such as rise time, overshoots, settling time, or steady state errors. The simulation results confirm the ability of Azadi controller to suppress the plant oscillations. Besides, the simplicity of Azadi controller with just three parameters with its good performances suggests Azadi controller to be a good candidate for any linear, nonlinear, or time varying plants

A LOW-COST APPROACH TO DATA-DRIVEN FUZZY CONTROL OF SERVO SYSTEMS

Servo systems become more and more important in control systems applications in various fields as both separate control systems and actuators. Ensuring very good control system performance using few information on the servo system model (viewed as a controlled process) is a challenging task. Starting with authors’ results on data-driven model-free control, fuzzy control and the indirect model-free tuning of fuzzy controllers, this paper suggests a low-cost approach to the data-driven fuzzy control of servo systems. The data-driven fuzzy control approach consists of six steps: (i) open-loop data-driven system identification to produce the process model from input-output data expressed as the system step response, (ii) Proportional-Integral (PI) controller tuning using the Extended Symmetrical Optimum (ESO) method, (iii) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller in terms of the modal equivalence principle, (iv) closed-loop data-driven system identification, (v) PI controller tuning using the ESO method, (vi) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller. The steps (iv), (v) and (vi) are optional. The approach is applied to the position control of a nonlinear servo system. The experimental results obtained on laboratory equipment validate the approach

Sensitivity Study of a Class of Fuzzy Control Systems

The paper performs the sensitivity study with respect to the parametric variations of the controlled plant in case of a class of fuzzy control systems dedicated to servo systems. The presentation is particularized to fuzzy control systems to solve the tracking control problem in case of wheeled mobile robots of tricycle type with two degrees of freedom. There is proposed a new development method for Takagi-Sugeno PI-fuzzy controllers based on the application of the Extended Symmetrical Optimum method to the basic linear PI controllers in a cascaded control system structure. There are derived sensitivity models, validated by considering a case study concerning the speed control of a servo system with DC motor as actuator in mobile robot control. Experimental results validate the development method for Takagi-Sugeno PI-fuzzy controllers

Understanding of tuning techniques of converter controllers for VSC-HVDC

A mathematical model of a voltage source converter is presented in the synchronous reference frame for investigating VSC-HVDC for transferring wind power through a long distance. This model is used to analyze voltage and current control loops for the VSC and study their dynamics. Vector control is used for decoupled control of active and reactive power and the transfer functions are derived for the control loops. In investigating the operating conditions for HVDC systems, the tuning of controllers is one of the critical stages of the design of control loops. Three tuning techniques are discussed in the paper and analytical expressions are derived for calculating the parameters of the current and voltage controllers. The tuning criteria are discussed and simulations are used to test the performance of such tuning techniques.reviewe

Comparison of Metaheuristic Optimization Algorithms for Quadrotor PID Controllers

In the present study, different solution methods are discussed in order to control the quadrotor with the most optimal PID parameters for the determined purposes. One of these methods is to make use of meta-heuristic algorithms in control systems. There are some limitations of using a PID controller as a classical construct. However, it is thought that more successful results will be obtained by optimizing its parameters through meta-heuristic algorithms. Initially, the mathematical model of the vehicle was created in MATLAB/Simulink. Then, genetic algorithms (GA), artificial bee colony (ABC), particle swarm optimization (PSO) and firefly algorithms (FA) were determined respectively as optimization methods. And these optimization methods used to determine the PID control parameters are applied to the developed mathematical model in the MATLAB/Simulink environment. In addition, the performances of the optimization methods are evaluated according to the comparison criteria. As a result of the comparison carried out according to ITAE (Integral Time Absolute Error) fitness criteria, ABC (1.2% - 4.4%) in terms of altitude, FA (4% - 13%) in terms of roll angle, GA (13% - %21) in terms of pitch angle, and PSO (4% - %15) in terms of yaw angle has been more successful than other methods

Optimal design of cascaded control scheme for PV system using BFO algorithm

In this paper presents Bacteria Foraging Optimization (BFO) algorithm based approach to find the optimum design values for the Proportional-Integral (PI) Controllers in cascaded structure is presented. Tuning the values of four PI controllers is very complex when the system is difficult to express in terms of mathematical model due to system nonlinearity. Response surface methodology (RSM) is used to formulate a mathematical design which is required to apply optimization algorithm. To examine the performance of BFO algorithm in obtaining optimum values of multiple PI controllers, a grid connected Photovoltaic (PV) system is chosen. Transient performance of the PI controller with optimum design values is evaluated under grid fault conditions. The system is simulated using PSCAD/EMTDC. Simulation results have shown the validity of the optimal design values obtained from RSM-BFO approach under different disturbances and system parameter variations

Theory, Simulation, and Implementation of Grid Connected Back to Back Converters Utilizing Voltage Oriented Control

This work presents a back to back converter topology with the ability to connect two power systems of different voltages and frequencies for the exchange of power. By utilizing indirect AC/AC conversion decoupling is achieved between the power systems with one of the three-phase, two-level voltage source converters performing the AC/DC conversion that maintains the required DC bus voltage level at unity power factor while the other converter operates in all four quadrants supplying/consuming active and/or reactive power with the other power system. The prototype implementation resides at UW-Milwaukee’s USR Building microgrid test bed facility. A possible application topology would be the converter that maintains the DC bus voltage to be connected to the microgrid’s electrical bus of distributed energy sources while the other converter is connected to the utility in order to supply the required active and/or reactive power to support the needs of the grid