Fixed Gain Proportional Integral Derivative Research Articles

Design of Vector Control Strategies Based on Fuzzy Gain Scheduling PID Controllers for a Grid-Connected Wind Energy Conversion System: Hardware FPGA-in-the-Loop Verification

This paper presents a hardware implementation upon a Field Programmable Gate Array (FPGA) of improved Vector Control Strategies (VCSs) based on a Fuzzy Logic System (FLS) of a grid-connected wind energy conversion system. Usually, the classical VCS is based on fixed-gain Proportional Integral Derivative (PID) controllers, which are known to exhibit limited performance against the nonlinear behavior of wind systems, such as rapid fluctuations of the wind speed and uncertainties of the system parameters. In order to overcome this limitation, an improved VCS based on Fuzzy Gain Scheduling PID controllers (VCS-FGS-PID) is suggested in this work to guarantee good tracking, high accuracy and good robustness under system parameter variations. Indeed, the PID controller gains are tuned, in real-time, by the FLS. In addition, the proposed VCS-FGS-PID methods are implemented on the FPGA in order to reduce the delays and the period of the system of the control loop, thanks to its parallel processing. In fact, the performance of the suggested VCS-FGS-PID approaches are proved by digital simulation with the Xilinx system generator tool under Matlab/Simulink, in addition to an experimental hardware-in-the-loop implementation using the FPGA. The obtained results demonstrate that the proposed VCS-FGS-PID techniques offer better performance as regards good tracking and high accuracy and good robustness against stator resistance variability compared to VCS-PI.

Intelligent Adaptive PID Control Using Fuzzy Broad Learning System: An Application to Tool-Grinding Servo control Systems

This paper presents an intelligent adaptive proportional-integral-derivative (PID) control method using fuzzy broad learning system (FBLS) and investigates how the method can be applied to control a tool-grinding servo control (TGSC) system. Due to accuracy, quality and geometric errors which are often difficult to capture the dynamics of the controlled plants or systems, fixed-gain PID controllers without good three-term parameters cannot meet the stringent control performance specifications of nonlinear industrial systems and servomechanisms. To accomplish better control, an adaptive PID control strategy based on the FBLS, or abbreviated as FBLS-APPID, is rigorously proposed by integrating an online parameter learning FBLS identifier together with an adaptive predictive PID control law using FBLS, to eliminate tracking error and achieve fast-tracking and disturbance rejection. Numerical simulations on the two existing discrete-time nonlinear time-delay processes are performed to show the merits and superiority of the constructed FBLS-APPID by comparing to three existing adaptive PID methods. Finally, the applicability of the proposed method is well exemplified by conducting comparatively experimental results on a servo control loop of a real TGSC machine with fixed PID gains tuned by the proposed FBLS-APPID method.

Nonlinear displacement control of magnetic material actuators

Magnetic polymer composites (MPCs) are soft material actuators capable of large deformation and fast response. They are wirelessly actuated and do not require onboard electronics or a power supply. Despite MPCs potential, the accuracy and reliability of controlling material displacement is unknown. This paper investigates the performance of three controllers for MPC position tracking: open-loop, fixed gain proportional-integral-derivative (PID) and gain scheduled PID. A systematic workflow, from plant identification to controller gain tuning, is presented, as well as a comprehensive experimental analysis of each controller. Due to observed nonlinear behavior, open-loop and fixed gain PID control were inadequate for fast, accurate position tracking. Gain scheduled PID presented a viable and efficient option for closed-loop displacement control.

Vehicle Speed Control Using Gain Scheduling PID with Experimental Throttle-in-the-Loop

This paper presents a control strategy for controlling speed of a vehicle experiencing the disturbance from road gradient. A non-linear vehicle longitudinal model is developed as plant for modelling the vehicle behaviour in longitudinal direction with Electronic Throttle Body (ETB) is introduced as the inner-loop subsystem. The vehicle is subjected to several positive (uphill) road gradient disturbances with gain scheduling Proportional-Integral-Derivative (PID) controller is proposed to control the vehicle speed. The simulation result is then validated using experimental throttle-in-the-loop method. MATLAB-SIMULINK is chosen as a simulation tool to simulate the vehicle dynamics behaviour and evaluate the performance of the control structure. The result shows that the proposed controller is able to effectively control the vehicle speed by reducing the speed drop during uphill travel and its performance is much better than fixed gain PID controller. The simulation results agree well with experimental.

Vehicle Speed Control Using Gain Scheduling PID Controller

This paper presents a control strategy for controlling speed of a vehicle experiencing the disturbance from road gradient using simulation method. A non-linear vehicle longitudinal model is used for modeling the vehicle behavior in longitudinal direction and the vehicle is subjected to several positive (uphill) road gradient disturbances. The gain scheduling Proportional-Integral-Derivative (PID) controller is proposed to achieve the control objective. MATLAB-SIMULINK is chosen as a simulation tool to simulate the vehicle dynamics behavior and evaluate the performance of the control structure. The result shows that the proposed controller is effective in controlling the vehicle speed with relatively lower speed drop. The controller performance is far better than the fixed gain PID controller.

Industrial experience of process identification and set-point decision algorithm in a full-scale treatment plant

This paper presents industrial experience of process identification, monitoring, and control in a full-scale wastewater treatment plant. The objectives of this study were (1) to apply and compare different process-identification methods of proportional-integral-derivative (PID) autotuning for stable dissolved oxygen (DO) control, (2) to implement a process monitoring method that estimates the respiration rate simultaneously during the process-identification step, and (3) to propose a simple set-point decision algorithm for determining the appropriate set point of the DO controller for optimal operation of the aeration basin. The proposed method was evaluated in the industrial wastewater treatment facility of an iron- and steel-making plant. Among the process-identification methods, the control signal of the controller's set-point change was best for identifying low-frequency information and enhancing the robustness to low-frequency disturbances. Combined automatic control and set-point decision method reduced the total electricity consumption by 5% and the electricity cost by 15% compared to the fixed gain PID controller, when considering only the surface aerators. Moreover, as a result of improved control performance, the fluctuation of effluent quality decreased and overall effluent water quality was better.

Development of linear models of Static Var Compensators suitable for enhancing performance of power systems including wind farms

In this work, the design of fixed-gain Proportional?Integral?Derivative (PID) controllers with multiple stage lead-lag compensators are investigated for improving further the dynamic impact of Static Var Compensators (SVCs). The analysis is based on the linearisation of the power system under study and the proper shift of critical eigenvalues, associated with the SVC and electric network, to the desired locations. In order to linearise the SVC an established fourth order model is used and the development of more complex models is attempted. This study deals with the development procedure of two different high order models for the SVC. Finally, one of them is adopted along with the fourth order model in order to design two different fixed-gain PID controllers with the multiple stage lead-lag compensator. The suitability and effectiveness of the resulted fixed-gain PID controllers is tested by performing digital simulations of a Greek power system including a wind farm under investigation.

Damping of generator oscillations using an adaptive static VAR compensator

Design of a static voltampere reactive (VAr) controller (SVC) using a novel adaptive scheme is investigated. The proposed controller, which makes use of self-tuning proportional-integral-derivative (PID) control, can provide better damping characteristics than a fixed-gain PID control SVC over a wide range of operating conditions. The system considered is a synchronous generator connected to an infinite bus through a double circuit transmission line. Digital simulations of the system following a three-phase fault under different loading conditions were performed to demonstrate the robustness and effectiveness of the controller.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>