Design Of Self-tuning Controller Research Articles

Design of an Implicit Self-tuning PID Controller Based on the Generalized Output

PID controllers have been widely employed in real processes. Since PID parameters strongly affect the control performance, lots of schemes for tuning PID parameters have been proposed. Fixed PID controllers are applied mainly. However, it is impossible to obtain good control performance for time-variant systems by the fixed PID controllers. Therefore, it is important to tune PID parameters in an on-line manner. In addition, especially in process systems, it is difficult to disturb the systems to identify. Since, it is important to determine PID parameters directly from the closed-loop operating data. In this paper, in order to overcome these problems, an implicit self-tuning PID control scheme is proposed. In the proposed method, a new parameter tuning law using obtained closed-loop data is introduced, and recursive least squares method is applied to the scheme. This scheme has a reference model which can be designed by users. As a result, the system output can track the desired reference model output. The new parameter tuning law can calculate PID gains directly from closed-loop data, so the proposed method belongs to implicit schemes. Therefore, a system identification can be avoided. In addition, procedures of the scheme are very simple. Hence, the computation cost becomes low. The effectiveness of the control scheme is evaluated by an experimental example.

Self-Tuning Robust Fuzzy Controller Design Based on Multi-Objective Particle Swarm Optimization Adaptation Mechanism

In this paper, an adaptive fuzzy controller design methodology via multi-objective particle swarm optimization (MOPSO) based on robust stability criterion is proposed. The plant to be controlled is modeled from its input–output experimental data considering a Takagi–Sugeno (TS) fuzzy nonlinear autoregressive with exogenous input model, by using the fuzzy C-means clustering algorithm (antecedent parameters estimation) and the weighted recursive least squares (WRLS) algorithm (consequent parameters estimation). An adaptation mechanism as MOPSO problem for online tuning of a fuzzy model based digital proportional-integral-derivative (PID) controller parameters, based on the gain and phase margins specifications, is formulated. Experimental results for adaptive fuzzy digital PID control of a thermal plant with time-varying delay are presented to illustrate the efficiency and applicability of the proposed methodology.

Intelligent Controller Design for Quad-Rotor Stabilization in Presence of Parameter Variations

The paper presents the mathematical model of a quadrotor unmanned aerial vehicle (UAV) and the design of robust Self-Tuning PID controller based on fuzzy logic, which offers several advantages over certain types of conventional control methods, specifically in dealing with highly nonlinear systems and parameter uncertainty. The proposed controller is applied to the inner and outer loop for heading and position trajectory tracking control to handle the external disturbances caused by the variation in the payload weight during the flight period. The results of the numerical simulation using gazebo physics engine simulator and real-time experiment using AR drone 2.0 test bed demonstrate the effectiveness of this intelligent control strategy which can improve the robustness of the whole system and achieve accurate trajectory tracking control, comparing it with the conventional proportional integral derivative (PID).

Self-tuning PID controller design using fuzzy logic for half car active suspension system

A car active suspension system plays an imperative role in adequately guaranteeing the stability of the car, retaining the continuous road wheel contact and improving the suspension performances. In this paper, Proportional Integral Derivative (PID), fuzzy logic and $$\hbox {H}\infty $$ controllers are used to control the car suspension system based on half car model. Moreover, a self-tuning PID controller based on fuzzy logic is developed to improve the performance of the system. The proposed structure overcomes the difficulty of having suitable responses in controlling the process in all conditions, especially when the system parameters are changing. The controllers are designed based on the mathematical model of the system. Through the proposed method, suspension working space is minimized and the best comfort of the driver is achieved. The comparison between simulation results demonstrates that by applying the presented method, the performance of the suspension system will be improved significantly.

Real-time implementation of four-phase interleaved DC–DC boost converter for electric vehicle power system

This paper proposes an advanced online self-tuning controller design for Four Phase Interleaved Boost Converter (FP-IBC), which is based on MATLAB-dSPACE Real-Time Interface Libraries (MLIB/MTRACE). The proposed controller consists of a Self-tuning Lead-Lag Compensator (SLLC) designed using Small-Signal Model (SSM). The controller’s parameters are tuned online to achieve fast convergence and good tracking response when parameters vary. The converter along with its advanced controller is tested experimentally at different loading conditions using two different power sources, i.e., Super-capacitor (SC) and battery modules. The experimental results show that the dynamic response of FP-IBC is significantly improved based on the proposed control design.

이동로봇 선회를 위한 Type-2 Fuzzy Self-Tuning PID 제어기 설계 및 조향각 제어

이동로봇 선회를 위한 Type-2 Fuzzy Self-Tuning PID 제어기 설계 및 조향각 제어

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

ABSTRACTThis paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton–Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.

A Self-Tuning zSlices-Based General Type-2 Fuzzy PI Controller

The interval type-2 fuzzy Proportional-Integral (PI) controller (IT2-FPI) might be able to handle high levels of uncertainties to produce a satisfactory control performance, which could be potentially due to the robust performance as a result of the smoother control surface around the steady state. However, the transient state and disturbance rejection performance of the IT2-FPI may degrade in comparison with the type-1 fuzzy PI (T1-FPI) counterpart. This drawback can be resolved via general type-2 fuzzy PI controllers which can provide a tradeoff between the robust control performance of the IT2-FPI and the acceptable transient and disturbance rejection performance of the type-1 PI controllers. In this paper, we will present a zSlices-based general type-2 fuzzy PI controller (zT2-FPI), where the secondary membership functions (SMFs) of the antecedent general type-2 fuzzy sets are adjusted in an online manner. We will examine the effect of the SMF on the closed-system control performance to investigate their induced performance improvements. This paper will focus on the case followed in conventional or self-tuning fuzzy controller design strategies, where the aim is to decrease the integral action sufficiently around the steady state to have robust system performance against noises and parameter variations. The zSlices approach will give the opportunity to construct the zT2-FPI controller as a collection of IT2-FPI and T1-FPI controllers. We will present a new way to design a zT2-FPI controller based on a single tuning parameter where the features of T1-FPI (speed) and IT2-FPI (robustness) are combined without increasing the computational complexity much when compared with the IT2-FPI structure. This will allow the proposed zT2-FPI controller to achieve the desired transient state response and provide an efficient disturbance rejection and robust control performance. We will present several simulation studies on benchmark systems, in addition to real-world experiments that were performed using the PIONEER 3-DX mobile robot that will act as a platform to evaluate the proposed systems. The results will show that the control performance of the self-tuning zT2-FPI control structure enhances both the transient state and disturbance rejection performances when compared with the type-1 and IT2-FPI counterparts. In addition, the self-tuning zT2-FPI is more robust to disturbances, noise, and uncertainties when compared with the type-1 and interval type-2 fuzzy counterparts.

Design and Analysis of a Self-Tuning Speed Controller for Permanent Magnet Synchronous Motors Based on the Neural Network

Design and Analysis of a Self-Tuning Speed Controller for Permanent Magnet Synchronous Motors Based on the Neural Network

Embedded Adaptive Self-Tuning Control Development by a Free Toolchain

In this study, we present an adaptive self-tuning controller (STC) design for small embedded systems. The new free tool-chain for model based control design is based, among other software, on the open simulator Scilab-XCos. After a very short introduction of model based design terms, this article focuses on the code generator and the other pro- grams of the tool-chain. The design concept is demonstrated by the non-trivial adaptive self-tuning control (STC) of the cart system in simulation and on a real laboratory experiment.

The Design and Simulation of Fuzzy PID Parameter Self-tuning Controller

Based on parameter self-tuning fuzzy PID controller, a fuzzy inference method is utilized to realize automatic regulating PID parameter, and the application of the controller in a system is studied with MATLAB in this paper. The combination of PID controller system and fuzzy controller system combines the convenience of PID control together with the flexibility of fuzzy control, and takes advantage of the traditional control, which has a great practical significance. The results of simulation show that fuzzy PID parameter self-tuning controller has a better control effect than the traditional one, and can improve the static and dynamic properties of the system well. DOI: http://dx.doi.org/10.11591/telkomnika.v14i2.7674

BP Neural Network for Mobile Robot Self-Tuning PID Controller Design

Establish the attitude model for self-designed mobile robot, According to the characteristics of nonlinear, unstable, using BP neural network method to achieve self-tuning PID parameters to make optimal parameters of the PID controller. Stabilization control of two-wheeled self-balanced robots at the same time, decrease the overshoot of the system and the number of shocks. Simulation experiments show that: Using BP neural network self-tuning PID controller improves system stability, effectiveness has been well controlled, with high practical value

Design and experimentation of a self-tuning PID control applied to the 3DOF helicopter

Abstract The paper presents design and experimental validation of a stable self-tuning PID controller for three degrees of freedom (3-DOF) helicopter. At first, it is proposed a self-tuned proportional-integral-derivative (PID) controller for a class of uncertain second order multiinput multi-output nonlinear dynamic systems to which the 3-DOF helicopter dynamic model belongs. Within this scheme, the PID controller is employed to approximate unknown ideal controller that can achieve control objectives. PID controller gains are the adjustable parameters and they are updated online with a stable adaptation mechanism designed to minimize the error between the unknown ideal controller and the used by PID controller. The stability analysis of the closed-loop system is performed using Lyapunov approach. It is proven that all signals in the closed-loop system are uniformly ultimately bounded. The proposed approach can be regarded as a simple and effective model-free control since the mathematical model of the system is assumed unknown. Experimental results are presented to verify the effectiveness of the proposed controller.

Research of Fuzzy PID Control Based on VHDL

This paper describes the use of VHDL and fuzzy controller design process.Compared with conventional PID control, fuzzy control is not dependent on the accurate mathematical model of the controlled object. The implementation of integrated practical operating experience and the operation is simple, fast response, anti-interference ability, strong robustness parameters of controlled object. In response to the limitations of the traditional PID control algorithm in the control field, the fuzzy control theory with the traditional PID control algorithm by combining the parameters self-tuning function, the proposed fuzzy self-tuning PID controller design method and algorithm-depth study analysis.

Missile Autopilot Design Based on Fuzzy Self-Tuning Immune PID Control

A design of the fuzzy self-tuning immune PID controller is proposed. The controller, which combines immune feedback mechanism and fuzzy PID control, executes the self-tuning of PID parameters in the control system. A simulation experiment is presented in light of a tactical missile autopilot transfer function. Simulation result shows that the performance of fuzzy self-tuning immune PID controller is better than that of fuzzy PID controller, especially in its robust performance for variable parameter system.

Based on the MATLAB Self-Tuning Fuzzy PID Controller Design

Based on MATLAB self-tuning fuzzy PID controller design, the line parameter of the PID controller to adjust, to further improve the performance of the PID controller to adapt to changes in the control object parameters changes and working conditions.Introduction

Single Degree Vibration Platform Self-Tuning Fuzzy PID Controller Design Based on AMESim

In recent years, hydraulic simulation has become an important means to research hydraulic system, in order to enable the single degree platform vibration curve with better traceability and reach the requirement of the test, this paper represent single degree system platform stimulated by simulation software AMESim, taking the Single degree freedom vibration hydraulic system as an example, MATlab/simulink is applied to the design of the vibration platform system fuzzy PID controller. Through the comparison between the simulation test and traditional PID controller, the designed self-tuning fuzzy controller can control the platform better, with smaller overshoot, faster response, shorter adjusting time, as well as fulfill the permissible accuracy.

Design and Simulation of Fuzzy Self-Tuning PID Controller for Two-Link Robot

In this paper, fuzzy self-tuning controller is introduced first. The fuzzy model is built according to the experience of PID parameter tuning with fuzzy set theory. Parameter tuning is achieved by use of fuzzy ratiocination and decision according to actual response, which is applied for control towards robot. Mathematical model of two-link robot has been built as well as its geometric and dynamical equations through coordinate transformation and matrix operation. Finally, fuzzy PD controller with self-tuning method is applied to realize control towards robots. Simulation in Matlab has been carried out whose result shows that the control method proposed in this paper has better performance than the traditional ones.

Design of fuzzy self-tuning PID controller based on field programmable analog array

To improve the response rate of process control,a method for hardware implementation of fuzzy self-tuning PID controller based on Field Programmable Analog Array(FPAA) was proposed.All cell circuits such as analog multiplier,seeking small and sum,divider were implemented on 8 AN221E04s,and then an intact controller was assembled with the cell circuits.As a hardware circuit,this controller has a better real-time quality than that of the fuzzy PID controller based on software programming;As an analog circuit,it does not need to be equipped with A/D and D/A conversion circuit because all of the internal transmission signals in this controller are analog values.Compared with digital circuit based fuzzy PID controllers,this controller has the features of simpler structure and faster operation.The experimental results show that fuzzy self-tuning PID controller based on FPAA has small over modulation and steady-state error,and the response time is brought down to microseconds.

Design of self-tuning controllers for highly non-linear mechatronic systems

A new procedure for design of self-tuning adaptive controllers (e.g., PID, lead-lag and in general n th order linear controllers) for use with highly non-linear mechatronic systems of the sort encountered in robotic and servomechanism control is developed. The procedure is presented in an algorithmic format. Describing function models, using analytical or experimental techniques, are used to determine the structure of the approximating linear plant at various operating regimes. The parameters of this linear structure are identified (using any available identification scheme) followed by obtaining the parameters of the linear controller by solving a set of simultaneous linear algebraic equations in real time. The procedure is demonstrated for design of self-tuning PID and lead-lag controllers for a non-linear plant of the sort encountered in servomechanism. It is shown that results are better than a fixed gain linear PID controller, and they compete with designs involving a non-linear PID and a non-linear ...