Fuzzy Immune PID Research Articles

A Robust LQR-Based Fuzzy-Immune PID Applied for a Greenhouse Temperature Networked Control

Bioinspired control system strategies have received considerable attention in recent years, demonstrating their effectiveness to control various classes of systems. This paper presents a new robust LQR-based fuzzy-immune PID controller synthesis method, the particularity of this structure is the combination of the features granted by the linear quadratic regulator LQR and the fuzzy-immune PID controller as: robustness, optimization and self-adapting. The proposed approach is applied to the temperature control of a greenhouse system over Ethernet network. Such control loop is bound to be affected by several uncertainties such as communication delays, packet dropout... etc., it is therefore necessary to adopt a robust control strategy that can handle these problems. MATLAB/Simulink is used to simulate the proposed controller structure under several perturbations/uncertainties scenarios. The results show better time domain performance and greater robustness against uncertainties, in comparison with other PID structures (classic and fuzzy immune PID).

Identification and Control of Elongation System of Skin Passing Mill Based on Intelligent Algorithm

In view of the nonlinear, time-varying and time-delay characteristics of elongation control system of skin pass mill, according to analysis of the mechanism model of elongation control system of skin pass mill, BP neural network was used to identify the structural parameters of the model. With reference to the regulating function of biological immune system and the function of fuzzy reasoning logic which can approach nonlinear function, a fuzzy immune PID control strategy was proposed to improve the elongation control accuracy of skin pass mill combining fuzzy control and immune feedback mechanism with traditional PID control. The simulation results show that the control strategy has the advantages of small overshoot, fast response, strong anti-interference ability and robustness, and the control effect is better than the traditional control method.

Publisher’s Note: “Application of genetic fuzzy immune PID algorithm in cruise control for commercial vehicles” [AIP Adv. 10, 095007 (2020)

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Application of genetic fuzzy immune PID algorithm in cruise control for commercial vehicles

Cruise control when driving downhill is one of the most important functions of commercial vehicles equipped with an auxiliary brake system. A genetic fuzzy immune PID algorithm is proposed to achieve a constant speed in this study. An immune feedback algorithm is used to adjust the proportional coefficient, and the fuzzy algorithm is used to adjust the integral coefficient and the differential coefficient. At the same time, the genetic algorithm is used to optimize the immune parameters to overcome the problem of improper selection of immune parameters, which results in large system overshoot and slow response. Simulation and experiment were also carried out to verify the effectiveness of the algorithm. The results show that the vehicle can keep the speed within ±2 km/h around the target speed. The analyses of lateral kinetic energy and the β phase-plane of both a tractor and a semitrailer indicate that braking stability is good when switching the retarder gear, which means the algorithm has a significant effect.

NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System

Automatic train operation (ATO) system is one of the important components in advanced train operation control systems. Ideal controllers are expected for the automatic driving function of ATO systems. Aiming at the intelligence requirements of the systems, an NSGA-II-based parameter tuning method for the fuzzy immune PID (FI-PID) controller and a grey model GM(1,1)-based fuzzy grey immune PID (FGI-PID) controller were proposed. Taking a maglev train’s model as the control object and a velocity-time curve as the input, the feasibility of the parameter tuning method for the FI-PID controller and the applicability of the FI-PID controller and the FGI-PID controller for the ATO system were tested. The results showed that the optimized parameters were ideal, the two controllers all showed good performance on the indicators of traceability and comfort level, and the FGI-PID controller performed better than the FI-PID controller. The results exhibited the effectiveness of the proposed methods.

A Design of Fuzzy Immune PID Controller for Six-rotor UAV Under Gyroscopic Effect

The six-rotor UAV has the characteristics of vertical take-off and landing, air hovering and large carrying capacity, which can accomplish tasks that cannot be completed by many fixed-wing aircrafts. In recent years, the research of dynamic modelling and control methods of the six-rotor UAV has gradually become hot topics at home and abroad. Considering the gyroscopic effect of the blade, a more accurate dynamic model of the six-rotor UAV is established, and then combined with the feedback mechanism of the biological immune system and the fuzzy control theory, a fuzzy immune PID controller is designed to optimize the parameters of the traditional PID controller, which can perform self-tuning of PID parameters. The position and attitude control of the UAV under hovering state is simulated by Matlab/Simulink software. The results show that compared with the conventional PID controller and fuzzy PID controller, the control system has the advantages of better dynamic and static performance such as shorter response time, smaller overshoot and improves the anti-interference ability and robustness of the system.

Immune Feedback Strategy in an Electronic Throttle Control System

The control strategy for improving the emission performance of engine transition condition is explored to enhance the dynamic response characteristics of the electronic throttle control system of automobile engines. A strong nonlinear relationship exists among the return spring, gear backlash, throttle shaft, and throttle body friction of the electronic throttle electromechanical system, thereby affecting the dynamic response characteristics of the engine electronic throttle under various operating conditions. On the basis of the nonlinear electronic throttle electromechanical system, a corresponding mathematical model is established to study the electronic throttle control system. Then, fuzzy and immune feedback control algorithms are applied to the motion control of the electronic throttle system on the basis of intelligent control because of its advantages of strong anti-disturbance ability, strong robustness, and applicability to nonlinear control systems. The immune feedback control algorithm is characterized by a rapid response in the control system. The influence of nonlinearity of the electronic throttle system on the control effect is discussed in this paper. The fuzzy immune PID controller is designed on the basis of the classical control algorithm PID for control precision and response of the system. The fuzzy control algorithm's adaptability to the nonlinear system improves the response performance of the electronic throttle system, and the immune feedback algorithm enhances the response efficiency of the control system. The response characteristics of electronic throttle is further explored. Experimental results show that the response speed of the fuzzy immune PID control system and speed adjustment of the dynamic characteristics of indicators have clear advantages over those of the PID and fuzzy PID control system. The controller is conducive to the improvement of the electronic throttle response characteristics. Improving the power, economy, and emissions of vehicles has important significance.

New Smith predictive fuzzy immune PID control algorithm for MIMO networked control systems

Aiming at the problem of network-induced delays for multi-input multi-output networked control systems (MIMO NCS), a new Smith predictive fuzzy immune PID algorithm is introduced to effectively reduce the adverse effect of network-induced delays about stability in MIMO NCS, firstly, by using the v-norm type to decouple the coupling plant. Based on the generalized plant after decoupling, the new Smith predictor is designed. Then, an modified fuzzy immune feedback control algorithm is used to tune PID controller parameters online. When there is a model mismatch or parameter perturbation, the set-point tracking performance and robustness of output response can be significantly optimized. The proposed algorithm does not contain the network delay prediction model and does not need to measure, estimate, or identify the network delay. It can be used in MIMO NCS where the network bandwidth is constrained and the network-induced delays are large. Numerical examples with Ethernet protocol are built to illustrate the correctness and effectiveness of this new algorithm.

Optimal Fuzzy-Immune Fractional PID Control Scheme for Path Tracking of Robot manipulator

This paper explains a new control structure based on theartificial immune system, Fuzzy and fractional order PIDcontrol schemes. In this paper immune feedback controlsystem, Fuzzy logic and fractional order control schemes will becombined and optimized using clonal selection algorithm.Fuzzy-immune fractional order PID Control schemes will beused as a new controller for path tracking of the robotmanipulator. The performance of the proposed control schemeis compared with fuzzy-immune PID control schemes. Theparameters of fractional PID and conventional PID controllersare optimized using Clonal Selection Algorithm (CSA).Simulation results state that optimal Fuzzy-immune fractionalPID is better than optimal fuzzy-immune PID Control schemesfor path tracking problem under the same condition. All controlschemes were tested using SIMULINK under MATLAB2014a

Research on Fuzzy Immune Self-Adaptive PID Algorithm Based on New Smith Predictor for Networked Control System

We first analyze the effect of network-induced delay on the stability of networked control systems (NCSs). Then, aiming at stochastic characteristics of the time delay, we introduce a new Smith predictor to remove the exponential function with the time delay in the closed-loop characteristic equation of the NCS. Furthermore, we combine the fuzzy PID algorithm with the fuzzy immune control algorithm and present a fuzzy immune self-adaptive PID algorithm to compensate the influence of the model deviation of the controlled object. At last, a kind of fuzzy immune self-adaptive PID algorithm based on new Smith predictor is presented to apply to the NCS. The simulation research on a DC motor is given to show the effectiveness of the proposed algorithm.

Study on Fuzzy Immune PID Controller for Main Steam Pressure Control System in Marine Steam Power Plant

The main steam pressure control system in marine steam power plant has the characteristics of time-varying, nonlinear and strong coupling. In order to get satisfactory control effect, we propose a fuzzy immune PID controller with which we can make comprehensive utilization of advantages of artificial immune, PID and fuzzy controller. We build up mathematical model of main steam pressure control system, carry out simulation and comparison. The results prove that fuzzy immune PID controller can significantly reduce the overshoot and settling time of main steam pressure. It is more effective in main steam pressure control system than PID controller.

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Application of Fuzzy Immune PID Controller Based on Particle Swarm Optimization in Power Plant Steam Temperature Control System

Power plant steam temperature control has characteristics of long delay and great inertia, a new method is proposed by analyzing above-mentioned problems and existing control methods on this paper. The method consists of an improved particle swarm optimization algorithm and a fuzzy immune PID controller. In addition, simulation results of PID, traditional fuzzy immune PID and fuzzy immune PID based on PSO are presented and compared. Fuzzy immune PID Control based on PSO has advantages of short adjustment time, quicker response time, better anti-interference ability and more stability. It can reduce the fluctuation of power plant steam temperature, and has better control performance and practical value.

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Optimal Tuning of a Fuzzy Immune PID Parameters to Control a Delayed System

Research on Temperature Control System of Fruit and Vegetable Processing Line Based on Fuzzy Immune PID

Temperature control has direct effect on mouth feel of fruit and vegetable processing products. This paper, by analyzing the control requirements of cucumber slices processing water temperature, proposes to control the water temperature for cucumber slice processing production line by using fuzzy immune PID. With the features of time-varying, nonlinear and hysteretic nature for temperature control, this paper designs fuzzy immune PID controller by borrowing the regulating action of immune system and linking the advantages of immune PID controller.

Study on Improved Fuzzy Immune PID Controller for Maglev Transportation System with Track Irregularity

Track irregularity is one of the most important aspects of the suspension control performance impact in maglev transportation system (MTS). Due to the track irregularity phenomenon of suspension system, the Fuzzy PID(F-PID) control is unable to accurately track irregularity of track changes. Based on the qualitative analysis to MTS, through modifying conventional F-PID controller, the article establishes Fuzzy Immune PID(FI-PID) Controller based on the biological immune system theory. The control strategy designed nonlinear P controller, using the immune algorithm of on-line adjustment of P and the fuzzy control approximating the nonlinear function of the immune P control parameters and the fuzzy control designed the ID controller for adjusting the parameters of I and D for enhancing the robust performance of the suspension system and adapting to the change of track irregularity. Simulation results show that the FI-PID control is confirmed more effectively to realize tracking compared with F-PID, faster response speed, more simple structure, easier operation for the track interference and load disturbance of the suspension system. This provides a very good way to solve the interference problem of orbit of the maglev transportation system.

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.