サポートベクターマシンによる切り替え構造を有するＰＩＤ制御系の一設計

The design and implementation of a multi-stage PID (MS-PID) controller for non-inertial referenced UAVs are highly complex. Symmetrical multirotor UAVs are unstable systems, and it is thought that the kinematics of the symmetrical UAV rotor, such as the quadrotor and hexacopter resembles the kinematics of an inverted pendulum. Several researchers have investigated the structure and design of PID controllers for high-order systems during the last decade. The designs were always concerned with the enhanced response, robustness, model reduction and performance of PID controllers. An accurate tuning process of such a controller depends on the engineer’s experience level. This is due to the number of variables and hyperparameters tuned during the process. An adaptive genetic algorithm (AGA) is utilized to optimize the MS-PID controllers for controlling the quadrotor in this study. The proposed method optimizes the offline-planned approach, providing several possibilities for adapting the controllers with various paths and or varying weather conditions. The MS-PID parameters are optimized in parallel, as every PID controller affects the other controller’s behavior and performance. Furthermore, the proposed AGA generates new chromosomes for “new solutions” by randomly developing new solutions close to the previous best values, which will prevent any local minima solution. This study intends to investigate the design and development of a highly tuned robust multi-stage PID controller for a symmetrical multirotor UAV. The work presents a model for a non-referenced inertial frame multirotor UAV (quadcopter). Once the model is defined, a robust multi-stage PID controller for the non-inertial referenced frame symmetrical multirotor UAV is designed, tuned, and tested. A genetic algorithm (GA) will be used to tune the MS-PID controller. Finally, the performance comparison between the proposed and conventional methods is presented. The results show that the proposed method provides stability improvement, better transient response, and power consumption.

In the paper recent design and tuning methods of PID controllers are summarized briefly. Several decades have seen the widely application of PID controllers and the design and tuning methods have been of considerable development. Process model identification, PID controller structure design, PID parameters tuning methods and the use and expansions of PID are described in turn. PID parameter tuning methods are highlighted.

A simple fuzzy rectification model based on mobile virtual reality technology based on PID parameters and mathematical modeling is reduced. In the PID control algorithm, parameter rectification is very important, which directly affects the control performance. The fixed parameters of the traditional method in some systems do not consider all the control indicators. Therefore, fuzzy control adjusts PID parameters and performs several experimental methods. The results show that the mobile virtual reality technology overadjusts the amount and rise time of the control system, when 5% of the response time, etc., are required; the parameters set by the ZN method cannot be taken into account. The PID parameter tuning method is practical in modern control and is an effective advanced method. This method has a certain adaptive ability, and the fuzzy control of PID parameters rectification based on mobile virtual reality technology can achieve a better control effect.

Evolutionary tuning of PID parameters

This paper introduces a novel structure to design a robust PID controller based on a Linear Matrix Inequality (LMI) approach. The objectives of the controller establishment are to achieve complete transparency and robust stability despite the large time-delay of communication channels and uncertainty in various parts of a teleoperation system. In this structure two local controllers must be implemented by applying an LMI-based H∞ theory. One of these controllers is responsible for tracking the master position in the remote site which is called slave controller. The slave controller is a novel robust PID controller which is implemented by employing an LMI-based H∞ framework. Furthermore, the other one controller called master controller is in charge of force tracking as well as guaranteeing stability of the closed-loop system and it requires to be established by applying an LMI-based multiobjective H2/H∞ method. Finding optimal values for the parameters of the controllers can be ensured by applying the convex optimization method in both sites. As it can be seen from the simulation results, the proposed control method is highly effective in providing a stable transparent teleoperation system under uncertain, but bounded, time-delay in communication channel and task environment. Since the simulation results illustrates time responses of the system for nominal values of the parameters, μ-analysis has been used to investigate stability of the overall system in spite of changes in the parameters of the master and/or slave manipulators in modified range.

Design of intelligent nonlinear robust controller for hydro-turbine governing system based on state-dynamic-measurement hybrid feedback linearization method

Inertial platform stabilization loop is required with good quickness, high steady precision, strong anti-jamming capability, etc. at the same time, and the traditional PID control is difficult to meet index requirements of the good control performance. Stabilization loop of inertial navigation system platform is treated as a study object, and the mathematical model is built with dynamic loop according to the position of PID controller. Based on the self-adaptive online genetic algorithm tuning, PID control strategy is proposed, and the PID parameters are optimized, and loop model is simulated with MATLAB software. The result of simulation shows that since PID controller is adopted after the genetic algorithm optimization, system control precision, stability and response speed have been improved, enhancing the robustness.

This paper proposes a novel method to graphically compute all feasible gain and phase margin specifications-oriented robust and optimal fractional PID controllers to stabilize time delay processes (TD) of any order. The gain-phase margin tester method is utilized to guarantee the concerned systems certain robust safety margins and test the constant gain margin boundary, constant phase margin boundary, and stability boundary in the parameter plane. The overlapping region of these plotted boundaries, which represents all feasible robust stabilizing PID controllers and allows the considered TD processes to retain pre-specified safety margins, is graphically determined as the gain and phase margin specifications-oriented region (GPMSOR). The variations of the GPMSOR and the stability region with respect to the variations of the noninteger orders of the integral and derivative terms have been investigated. According this, it is possible to slightly enlarge the GPMSOR by altering the noninterger order of the integral and derivative terms. This modifications in GPMSOR through altering the noninteger orders of the integral and derivative terms allows us to find the robust and optimal PID controller gain set for the considered TD systems. In other words, the selected fractional order PID controllers from the GPMSOR not only retain the prescribed GM and PM specifications but minimize the integral of the absolute error (IAE) or the integral of the squared error (ISE) performance criterion. Finally, an illustrative example cited from the literature with computer simulations is provided to demonstrate the effectiveness and confirm the validity of the proposed methodology.

We propose a robust self-tuning PID controller suitable for nonlinear systems. The control system employs a preload relay (P_Relay) in series with a PID controller. The P_Relay ensures a high gain to yield a robust performance. However, it also incurs a chattering phenomenon. In this paper, instead of viewing the chattering as an undesirable yet inevitable feature, we use it as a naturally occurring signal for tuning and re-tuning the PID controller as the operating regime digresses. No other explicit input signal is required. Once the PID controller is tuned for a particular operating point, the relay may be disabled and chattering ceases correspondingly. However, it is invoked when there is a change in set-point to another operating regime. In this way, the approach is also applicable to time-varying systems as the PID tuning can be continuous, based on the latest set of chattering characteristics. Simulation results for the level control of fluid in a spherical tank using the scheme are also presented.

A design method of enhanced robust fractional order PID controller is proposed to control electrical machinery system. Magnitude margin constraint, phase margin constraint and the gain robustness constraints of partly flat phase in specified dots around crossover frequency are adopted to design enhanced robust fractional order PID controller which has stronger robustness to open-loop gain variation compared with integer order PID controller. Besides, nonlinear optimization function is adopted to hunt for optimal parameter solutions of enhanced robust fractional order PID controller, so the five parameters of enhanced robust fractional order PID controller can be solved. The electrical machinery control system models are simulated and tested by MATLAB/SIMULINK, and the results show that the proposed fractional order PID controller has stronger robustness and smaller overshoot, compared with integer order PID controller.

PID controllers have been widely used in many industries. They can provide robust and reliable performance for most systems. However, it is well known that the automatic controlled systems are susceptible to faults and the faults can cause a malfunction of the loop. The main motivation in this paper is to present a design scheme of controllers using the least squares support vector machines (LS-SVM) which achieve to self-tune the parameters to compensate effects of the faults. This method used LS-SVM to learn system post-fault dynamics. The auto-tuning algorithm for PID controller is activated using the residual signal generated from the fault detection path. That is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The strategy is clarified with the aid of a well-regarded benchmark three-tank system with various faults.

PID controllers have been widely used in many industrial processes because they have only three control parameters, and we can easily understand their physical meanings. However, it is difficult to tune their parameters in the case where the control system has uncertainties, for example, modeling errors, system fluctuation, and so on. Therefore, we propose a design scheme of robust PID controllers. First, we design a PID controller based on the generalized minimum variance control (GMVC) scheme which is a self-tuning control strategy. Next, we present a method for the design of a weighting factor included in the cost function of GMVC from the viewpoint of robust stabilities. Finally, we discuss the application for an experimental air pressure control system.

Every process is having uncertainty, affects the performance of the system, even breakdown. Hence the uncertainty has to be analyzed seriously. In this paper, the parametric uncertainty is determined using multiple experiment method for a highly non linear plant. An unstable bioreactor is considered as a nonlinear process for the analysis. It is having various uncertainties in the process parameter. Substrate feed and surrounding temperature are the sources of external parametric uncertainty; also the specific growth rate and dilution rate are the internal parametric uncertainty. Overall uncertainty is determined using Monte Carlo method and the results were compared with the standard methods. Simulation results addresses that the effect of various uncertainties in the biomass concentration. A robust PID controller was designed for both stable and unstable conditions using Particle swarm optimization (PSO) algorithm, which control the system effectively when the uncertain parameter varies within the specified range. Controller performances were analyzed for various uncertainties range using MATLAB Simulink and estimated the sensitivity of each parameter individually and combined.KeywordsMonte Carlo uncertainty analysisbioreactorParticle swarm optimization

Robust control algorithms may improve the efficiency of wave power conversion systems since they present intrinsic nonlinear dynamics and the system uncertainties. Sometimes, the generators that can operate al variable speed (e.g. double feed induction generator) are used at wave power generation plants, since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimun flow coefficient value which improving its efficiency. This paper proposes a sliding mode controller for wave power plants based on a double feed induction generator. Also, the presented robust control scheme introduces an adaptive sliding gain that avoids calculating the upper bound for the uncertainties of the system, facilitating its application. The stability of the proposed control scheme is analyzed by means of the Lyapunov stability theory. Finally, the proposed control scheme is validated through some simulation examples.

A robust adaptive PID controller design motivated from the sliding mode control is proposed for a class of uncertain chaotic systems in this paper. Three PID control gains, \(K_p, K_i\), and \(K_d\), are adjustable parameters and will be updated online with an adequate adaptation mechanism to minimize a previously designed sliding condition. By introducing a supervisory controller, the stability of the closed-loop PID control system under with the plant uncertainty and external disturbance can be guaranteed. Finally, a well-known Vanderpol oscillator is used as an illustrative to show the efectiveness of the proposed robust a PID controller.