Globally stable discrete time PID Passivity-based Control of power converters: Simulation and experimental results

This study describes the technique for implementation of discrete-time PID controller for automatic voltage regulator. It is most significant to derive a controller implementation technique for discrete-time systems. A new PID design pattern will be suggested for the without causality complications by considering the equivalent PID controller. A very most popular controller is the discrete-time closed-loop PID controller. Discrete time PID controllers have very fast responses like rise time and peak overshoot, as compared to the continuous-time PID controller. While, we have to observe the stability in a continuous-time of some digital controller, we use the digital signals as an input to the computer; however after using z-transform to change the system to a digital control system and give these signals inside the microprocessor by the ATU; and after that convert them to analog to the final element. Keywords : AVR system, discrete time PID controller, ADC, DAC Cite this Article Ashish Mishra, Shekhar Yadav. Design of Discrete Time PID Controller. Journal of Operating Systems Development & Trends . 2019; 6(1): 14–22p.

Optimization and discrete fractional-order PID controller applied to a pressure swing adsorption plant for the production and recovery of bioethanol

Due to the low slip rate and poor braking performance of automobile anti-lock braking system, a discrete fuzzy adaptive PID control algorithm for automobile anti-lock braking system is designed in this paper. Based on the theory of discrete fuzzy adaptive PID control algorithm, the braking force of a vehicle is analyzed and the anti-lock control target is set. The automobile adhesion coefficient and wheel slip rate are calculated as the input and output of the PID control algorithm to complete the control of the anti-lock brake system of the network automobile. Experiments show that the sliding rate of the discrete fuzzy adaptive PID control algorithm of the designed anti-lock system is close to 20%, which proves that the design method has good braking effect.

This paper implements and compares the existing power supply converters for an energy storage system to determine the best suited for the smart grid application. A survey of different DC-DC converters is carried out to analyze the battery's overall performance. The main objective is to identify this application's most appropriate energy storage device. The advantages of this technology have high efficiency and reliability, which can connect various energy sources and reduce conduction losses in the power converters. Through the converter control, reference currents are imposed to charge the battery. The battery nominal voltage needs to change to see which type of converter is the most suitable and robust. Simulation results show that the operating ranges of boost-buck, buck-boost, and buck-boost converters with negative output voltage enhance the efficiency of battery and renewable energy sources and compared the DC converters to know the functional voltage for the energy storage system. The power converter's efficiency and control facility will allow us to link the energy storage system with the power grid. The overall installation is established using MATLAB/Simulink software.

The DC-DC converters are extensively used in modern telecommunication and consumer electronics. Stability is one of the most aspect in designing of automatic control of DC-DC buck converter. In this paper a discrete auto-tuning PID scheme is developed for DC-DC converters for fast response time. When the required output does not follow the set point, a controller for synchronous buck converter is to be used with objective of keeping the error as minimum. The algorithm is used for the tuning discrete PID controller to obtain its parameters with a minimum error and is applied to Synchronous buck converter to improve its performance. For fast transient response, settling time and rise time of the Converter, the controller gains are continuously modified. For its implementation a buck converter is designed and its MATLAB/Simulink model is developed. The simulation results describes the effectiveness of the developed algorithms.

In order to achieve a high-quality machining process with superior productivity, it is very important to tackle the phenomenon of chatter in an effective manner. The problems like tool wear and improper surface finish affect the milling process and are caused by self-induced vibration termed as chatter. A strategy to control chatter vibration actively in the milling process is presented. The mathematical modeling of the process is carried out initially. In this paper, an innovative technique of discrete time sliding mode control (DSMC) is blended with the type-2 fuzzy logic system. The proposed active controller results in a significantly high mitigation of vibration. The DSMC is linked to the time-varying gain which is an innovative approach to mitigate chattering. The theorem is laid down which validates that the system states are bounded in the case of DSMC-type-2 fuzzy. Stability analysis is carried out using Lyapunov candidate. The nonlinearities linked with the cutting forces and damper friction are handled effectively by using the type-2 fuzzy logic system. The performance of the DSMC-type-2 fuzzy concept is compared with the discrete time PID (D-PID) and discrete time sliding mode control for validating the effectiveness of the controller. The better performance of DSMC-type-2 fuzzy over D-PID and DSMC-T1 fuzzy in the minimization of milling chatter are validated by a numerical analysis approach.

In the paper, we introduce a continuous and discrete PID optimization method by using genetic algorithm (GA) to analyze and control antenna position – a typical model in control engineering. From analizing kinematic equations of this model, we propose continuous and discrete PID controllers to stabilize it. The control result in the case of the empirically selected K matrix (Kp, Ki, Kd) is compared to the case of the K matrix optimized by GA. From this, we can compare the system's output response with the above continuous and discrete PID controllers. The results show that continuously and discrete optimized PID controllers by GA are better than PIC controllers from empirical test through simulation.

This paper presents a new optimal tuning approach for discrete PI/PID compensators via Linear Quadratic (LQ) cost function by exploiting non-minimal state space (NMSS) form. In this regard, first order discrete-time transfer function (TF) of Bitumen system with samples time delays more than unity is utilized to formulate the novel NMSS-PI/PID form. The approach then develops state variable feedback (SVF) control law for PI/PID implementation on Bitumen system, sited at INSUMAT Company. The work also introduces proportionalintegral-plus (PIP) control as a well-established model-based, full state feedback control, when applied to the same Bitumen system, as benchmark. For consistent comparison, NMSS-PIP form is formulated using the same TF, then optimizing the PIP gains via LQ cost function. Here, the Bitumen temperature should not exceed ± 5% of the specified temperature (90o C-180o C) in order to achieve an accepted properties for the produced material. Moreover, overshoot behaviour is not allowed in order to avoid self-ignition for the vapor inside the Bitumen tank. Simulation results verify the applicability of the new discrete PID approach. Also both discrete PID and PIP control show satisfactory steady state response with good control action, with little significant improvement of PIP over new approach of discrete PID control. The paper shows successful implementation ‘onsite’ for the two controllers, for which all the control design criteria are met.

The combination of isolation system and active control devices has been increasingly considered in the structural control community to design an efficient smart hybrid baseisolation system for seismic protection. In this paper, a control scheme based on a combination of discrete PID controller and discrete direct adaptive neural controller is proposed for the active control of a nonlinear base isolated building to reduce superstructure responses and base drifts under near-fault earthquake excitations. Even though the PID controller is a traditional and widely used in many control applications, the performance of PID controller is not satisfactory in time varying and nonlinear systems. But the efficiency of its performance can be enhanced by combining the PID controller along with neural controller. The neural controller is constructed based on a single hidden layer feed forward network and the parameters of the network are modified using extreme learning machine (ELM) — like algorithm. To ensure the stability of the system, unlike original ELM algorithm, Lyapunov update law is used to update the output parameters of the network. This approach is validated by simulating a non-linear three dimensional benchmark base-isolated structure with time history records of three near-fault earthquakes. The performance of the proposed control scheme is measured in terms of a comprehensive set of performance indices. The results show that the proposed neural aided discrete PID active controller is more effective in reducing the superstructure acceleration, inter-storey drifts and base displacement by giving an active feedback control force to the base-isolated structure.

The papers in this special section focus on predictive control in power converters and electrical drives. With the fast microcontrollers available today, applications of predictive control in power converters and electrical drives are a very powerful and attractive alternative to classical controllers. The use of predictive control offers a number of advantages: very intuitive approach, no need for linear controllers and modulators, easy inclusion of nonlinearities and restrictions, etc. However, predictive control schemes in power converters and electrical drives have not yet been implemented in industrial applications. Nevertheless, after some further progress, it can be expected that the advantages of predictive algorithms will lead to an increased number of industrial applications in the future. The focus on this special is on: 1) predictive control applied to power converters; 2) predictive control applied to motor drives; 3) design and implementation issues of predictive control; and 4) applications of predictive control in industrial electronics.

In this study, a discrete fractional order PID controller for nonlinear systems is proposed. U-model is firstly employed to transform nonlinear systems into a linear-like model and model complexity is then degraded and easier for controller design. Then, a new discrete fractional order PID control law in difference equation is presented which takes advantage of two more adjustable parameters. Finally, robust stability of the control law is analysed. Both deterministic and stochastic examples are provided to illustrate the effectiveness and superiority of the proposed controller.

In this study, a DC-DC buck converter circuit which is used to get direct voltage by decreasing the source voltage is researched. Firstly mathematical model for a DC-DC buck converter circuit is obtained and critical inductance value is calculated to make it work in continuous current mode. Then for controlling a DC-DC buck converter, three different controllers in discrete time (sliding mode control, proportional–integral–derivative controller and linear quadratic regulator) are designed. Finally, the performance of these controllers according to changing in the form of step function for input voltage, reference voltage and load conditions are examined and compared with real time studies. According to obtained results, a DC-DC buck converter circuit controlled by sliding mode controller has shown a better performance compared to the other controllers.

In this paper, PID controller has been employed to suppress vortex induced vibration (VIV) on a marine riser cylindrical pipe in a good way. Neural Network time series (NNTS) have been represented as a nonlinear system identification to describe the dynamic response of the system after extracting the input-output data from previous paper which it collected from experimental setup. NNTS methods comprised three methods: Neural Network (NARX) based on the Nonlinear Auto-Regressive with External (Exogenous) Input, Neural Network (NAR) based on the Nonlinear Auto-Regressive and Nonlinear Input-Output Neural Network. The Discrete Time PID controller (DT- PID) based on heuristic methods has been chosen to attenuate the VIV on the best model of the three methods. Mean square Error (MSE) has been selected to validate from the nonlinear system identification and PID parameters. Finally, the outcomes showed that the NARX is the best method to represent the VIV on pipe riser from other methods which recorded least MSE= 1.2714×10-9 and DT-PID controller succeeded effectively to suppress vortex induced vibration for marine pipe risers under disturbance load.

This paper discusses discrete sliding mode control for two-link rigid robotic manipulators with uncertain modelling. The discrete sliding mode control problem is formulated. Necessary and sufficient conditions of stability along with the effect of sampling are stated. The discrete controller is shown to lead to a stable closed-loop system. Simulation results are presented to illustrate the features of the control scheme.

Quadrotor is a highly non-linear system with complex dynamics. For a stable flight, it requires an efficient control scheme. This paper first present a discrete PD, PI and PID controllers based control scheme. It is a simple control strategy, capable of controlling the quadrotor. This paper also presents the non-linear model predictive control of quadrotor. Model predictive control is a digital control technique and it uses plant model in order to find the control signals. Discrete non-linear model of quadrotor is used. The parameters of this discrete non-linear model are found by using the input output data of quadrotor taken from PID control simulation and recursive least squares (RLS) algorithm. The novelty of the proposed scheme lies in the use and parameter identification of non-linear model of quadrotor. Model predictive control is an optimal control strategy that provides optimal control signals by using constrained optimization and gives optimal control results. Simulation results have shown the effectiveness of the proposed control scheme.