Local PID Controllers Research Articles

Dynamic Behavior and Stability Analysis of Automatic Voltage Regulator with Parameter Uncertainty

This research article describes a novel optimization technique called simulink design optimization (SDO) to compute the optimal PID coefficients for an automatic voltage regulator (AVR). The time-domain performance of the proposed controller was analyzed using MATLAB/Simulation, and its performance was compared with that of water cycle algorithm, genetic algorithm, and local unimodal sampling algorithm-based PID controllers. The robustness of the proposed controller was verified by applying the disturbances to the generator field voltage and the amplifier parameter uncertainty. The studies presented in literature were discussed the AVR loop stability using the Bode plot which will not give the minimum stability margins. This study proposes a novel stability analysis called disk-based stability analysis to authenticate the stability of the AVR loop which is obtained by the classical analysis. This stability was compared with the proposed stability analysis. The MATLAB results reveal that the SDO-PID controller regulates the terminal voltage of the generator precisely, is more robust to parameter uncertainty, and is more stable than the other controllers. The maximum allowable parameter uncertainty of the amplifier model was identified as 102% of its nominal parameters. The stability margins are recognized as DGM = 10.40 dB and DPM = 56.50° for the AVR stability.

Adaptive Tuned Controller Parameters for Non-Linear Tanks

In this article, an adaptive PID controller design is proposes for the nonlinear conical tank process. The modeling of the proposed tank process is obtained from local linear modeling technique. Totally five local linear regions are identified and formed to get nonlinear model of the process. The PID controller is designed for each linear model and combined together to get the adaptive PID controller. The identified adaptive PID is presented to the conical system and the measured results are verified with local PID controllers to show the effectiveness of the proposed one. From the measured results, it is verified that the overall performance of the Adaptive PID controller is significantly better than local PID.

Design of PID Type Local Controller Network with Fuzzy Supervision

This paper proposes a feasible fuzzy strategy, network of local PID controllers type, applicable to the improvement of the dynamic stability and robustness of a well-known electromechanical system. Experimental tests confirm the superiority of the proposed method over classical control methods to treat nonlinearities and parametric variations of the plant.

Two-Layer Linear MPC Approach Aimed at Walking Beam Billets Reheating Furnace Optimization

In this paper, the problem of the control and optimization of a walking beam billets reheating furnace located in an Italian steel plant is analyzed. An ad hoc Advanced Process Control framework has been developed, based on a two-layer linear Model Predictive Control architecture. This control block optimizes the steady and transient states of the considered process. Two main problems have been addressed. First, in order to manage all process conditions, a tailored module defines the process variables set to be included in the control problem. In particular, a unified approach for the selection on the control inputs to be used for control objectives related to the process outputs is guaranteed. The impact of the proposed method on the controller formulation is also detailed. Second, an innovative mathematical approach for stoichiometric ratios constraints handling has been proposed, together with their introduction in the controller optimization problems. The designed control system has been installed on a real plant, replacing operators’ mental model in the conduction of local PID controllers. After two years from the first startup, a strong energy efficiency improvement has been observed.

局所的PID制御器を用いた1脚ロボットの姿勢制御

Although legged robots have been researched for more than 20 years, their movement is not quick as same as animals. Abilities of a leg are not clarified. The objective of this research is to clarify the abilities and functions by manufacturing a one-legged robot. The one-legged robot is designed as almost same as human legs. Since it has not only electric motors but air cylinders in its thigh and calf as actuators, it has enough power to move. Local PID controllers for body attitude and center of gravity work to stabilization of standing control for the one-legged robot.

Design and Application of a Data-Driven Expert Controller Based on the Operating Data of a Skilled Worker

[abstFig src='/00280005/16.jpg' width='300' text='Schematic of data-driven expert controller' ] In recent years, due to the mass retirement of skilled workers, loss of expertise has emerged as a problem in Japan. Meanwhile, the performance of computer hardware has been drastically improving. Skill-based PID controllers utilizing a database have been proposed as a potential solution to this problem. However, these controllers may not respond to multiple demands of control performance from users because the controller was not considered in the evaluation from the users. As a solution to this problem, an expert controller based on a skilled worker’s operating information with control performance assessments has been proposed. According to the method, I/O data, PID parameters that are estimated using the operating data and evaluation values of the skill of the skilled worker are stored in the database. From this, information vectors with high scores are selected, and a local PID controller is designed in response to the user’s requirements. In the conventional research, the least squares method is applied for estimating the PID parameters from the operating data of the skilled worker, and there are no restrictions on their values. This risks a loss of physical meanings of PID parameters in the case that they have negative values. In this research, an expert controller using particle swarm optimization (PSO) is proposed. In this method, data obtained by human control of a control simulator constructed on a computer is used to estimate human’s skill as PID parameters. Moreover, providing restrictions for the estimation of PID parameters enables them to preserve their physical meanings. In this research, the effectiveness of the proposed expert controller is verified using a control simulator.

Multi-region fuzzy logic controller with local PID controllers for U-tube steam generator in nuclear power plant

Abstract In the paper, analysis of multi-region fuzzy logic controller with local PID controllers for steam generator of pressurized water reactor (PWR) working in wide range of thermal power changes is presented. The U-tube steam generator has a nonlinear dynamics depending on thermal power transferred from coolant of the primary loop of the PWR plant. Control of water level in the steam generator conducted by a traditional PID controller which is designed for nominal power level of the nuclear reactor operates insufficiently well in wide range of operational conditions, especially at the low thermal power level. Thus the steam generator is often controlled manually by operators. Incorrect water level in the steam generator may lead to accidental shutdown of the nuclear reactor and consequently financial losses. In the paper a comparison of proposed multi region fuzzy logic controller and traditional PID controllers designed only for nominal condition is presented. The gains of the local PID controllers have been derived by solving appropriate optimization tasks with the cost function in a form of integrated squared error (ISE) criterion. In both cases, a model of steam generator which is readily available in literature was used for control algorithms synthesis purposes. The proposed multi-region fuzzy logic controller and traditional PID controller were subjected to broad-based simulation tests in rapid prototyping software - Matlab/Simulink. These tests proved the advantage of multi-region fuzzy logic controller with local PID controllers over its traditional counterpart.

Preparation of Papers for IFAC Conferences & Symposia: Integration of Process Design and Control Using Hierarchical Control Structure

The integration of process design and control (IPDC) has become increasingly important and received considerable academic and practitioner attention over the recent decades. Moreover, some works in the field have utilized advanced controllers into IPDC framework. Considering the fact that the hierarchical control structure which consists of local PID controllers and an advanced process control (APC) as the central controller has been used widely in industrial practice, in this paper, the two-level hierarchical control structure is taken into account within the IPDC framework for the first time. The IPDC problem using hierarchical control structure is formulated as a bi-level optimization problem, which separates the design decisions from the APC decisions and then keeps the problem size manageable. And the APC decisions are incorporated in a superstructure-based dynamic optimization formulation which considers both cost and controllability. A continuous stirred tank reactor is used to test the proposed IPDC methodology.

Multiloop control of a drum boiler

The Equivalent Subsystems Method (ESM) (Kozáková et al., 2011) is methodology of decentralized controller design in the frequency domain which allows designing local controllers using any SISO frequency domain method. The paper deals with the digital ESM version where digital local PID controllers guaranteeing required performance for the full system are designed for individual equivalent subsystems using the practice-oriented Sine-wave method (Bucz et al., 2012). The proposed decentralized controller design procedure was verified on the nonlinear benchmark drum boiler simulation model (Morilla, 2012).

Algorithm for Multiple Model Adaptive Control Based on Input-Output Plant Model

Abstract An algorithm for multiple model adaptive control of a time-variant plant in the presence of measurement noise is proposed. This algorithm controls the plant using a bank of PID controllers designed on the base of time invariant input/output models. The control signal is formed as weighting sum of the control signals of local PID controllers. The main contribution of the paper is the objective function minimized to determine the weighting coefficients. The proposed algorithm minimizes the sum of the square general error between the model bank output and the plant output. An equation for on-line determination of the weighting coefficients is obtained. They are determined by the current value of the general error covariance matrix. The main advantage of the algorithm is that the derived general error covariance matrix equation is the same as this in the recursive least square algorithm. Thus, most of the well known RLS modifications for the tracking timevariant parameters can be directly implemented. The algorithm performance is tested by simulation. Results with both SISO and MIMO time variant plants are obtained.

Design of a multiple linear models-based PID controller

Almost real-world plants are represented by non-linear systems. Therefore, it is important to consider PID control schemes to cope with such systems. In this paper, a PID control method for non-linear systems is newly proposed. Some local linear models on typical equilibrium points are first designed, followed by linear PID controllers corresponding to these models. The distances between the query and these local models are calculated, and the weights are computed in proportion to the distances. These weights are put for local PID controllers, and the PID controller corresponding to the query can be designed. According to the proposed scheme, the good PID control performance can be easily obtained. The effectiveness of the PID control scheme is illustrated by some simulation examples and experiment.

A Multiobjective Adaptive Controller for Magnetic Bearing Systems

The paper considers three issues in flexible rotor and magnetic bearing systems, namely, the control of rotor vibration, control of transmitted forces, and prevention of rotor contact with auxiliary bearings. An adaptive multiobjective optimization method is developed to tackle these issues simultaneously using a modified recursive adaptive controller. The proposed method involves automatic tuning of the weighting parameters in accordance with performance specifications. A two-stage weighting strategy is implemented, involving base weightings, calculated from a singular value decomposition of the system’s receptance matrices, and two adjustable weighting parameters to shift the balance between the three objective functions. The receptance matrices are functions of rotational speed and they are estimated in situ. The whole process does not require prior knowledge of the system parameters. Real-time implementation of the proposed controller is explained and tested by using an experimental flexible rotor magnetic bearing system. The rotor displacements were measured relative to the base frame using four pairs of eddy current displacement transducers. System stability is ensured through local PID controllers. The proposed adaptive controller is implemented in parallel, and the effectiveness of the weighting parameters in changing the balance between the transmitted forces and rotor vibrations is demonstrated experimentally.

Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor

In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.

Implementation of predictive controllers as outer-loop controllers

The implementation of predictive controllers as supervisory control systems is discussed. In this configuration, common in practice, the manipulated variables calculated by the predictive controller do not directly drive the actuators; instead, it is the command signals from the local PID controllers that drive the actuators that act on the physical system. This structure is known to perform less efficiently when the local controllers are re-tuned, because the model used in the predictive controller differs from the real one. Thus, performance decreases and might even lead to oscillations and instabilities of the overall control system. This paper presents a solution to this problem based on the use of an adequate two-degrees-of-freedom structure as an interface between the predictive controller and the local controllers, which makes the predictive controller robust against variations in the local controller. The application of this technique on a simulated industrial boiler achieves the following advantage: the performance of the predictive control system is maintained despite re-tuning of the inner-loop controller.

Adaptive and non-adaptive model predictive control of an irrigation channel

The performance achieved with both adaptive and non-adaptive Model Predictive Control (MPC) when applied to a pilot irrigation channel is evaluated. Several control structures are considered, corresponding to various degrees of centralization of sensor information, ranging from local upstream control of the different channel pools to multivariable control using only proximal pools, and centralized multivariable control relying on a global channel model.In addition to the non-adaptive version, an adaptive MPC algorithm based on redundantly estimated multiple models is considered and tested with and without feedforward of adjacent pool levels, both for upstream and downstream control. In order to establish a baseline, the results of upstream and local PID controllers are included for comparison. A systematic simulation study of the performances of these controllers, both for disturbance rejection and reference tracking is shown.

Local Linear PID Controllers for Nonlinear Control

Nonlinear PID design is difficult if one approaches the problem from a global design perspective. The authors propose coalescing the adaptive local linear modelling approach with traditional linear PID controller design techniques to arrive at a principled, intuitive, and simple nonlinear PID controller design methodology. The article, in particular, discusses two local linear modelling approaches, one based on competitive linear models attached to a self-organizing map and one based on cooperative linear models attached to the modes of a Gaussian mixture model. The system identification and closed-loop tracking performances of the proposed PID controller design methodology are demonstrated to be better than inverse and PID controllers for a global nonlinear system identifier and a global linear model, respectively.

Global control of a vibrating plate using a feedback-controlled inertial actuator

Strategies for the suppression of plate vibration are investigated by considering approximations to the equivalent impedance of power-minimizing vibration controllers. The total power transmitted to a plate by both a primary and a secondary point force is minimized and the equivalent impedance presented by the secondary source to the plate is considered. A novel device for active vibration control, based on an inertial actuator with displacement sensor and local PID controller and an outer velocity feedback control loop, is used to control the vibrating flexible plate. The impedance presented to the plate by this actuator is compared with the equivalent impedance of the optimal active control system. A frequency-domain formulation is used to analyse the stability and performance of an active vibration suppression system using this modified inertial actuator. The results of an experimental study of active vibration suppression on a flexible plate using the modified inertial actuator are then described. Theory and experiments agree well, demonstrating the effectiveness of the modified inertial actuator.

Active vibration isolation using an inertial actuator with local displacement feedback control

The design of inertial actuators with local displacement feedback control and their use in active vibration isolation systems is considered. Unlike reactive actuators, inertial actuators do not need to react off a base structure and can therefore be directly installed on a vibrating structure. However in order to guarantee good stability margins in the active isolation controller, the actuator resonance must have a low natural frequency and it must be well damped. However, the need to have an inertial actuator with a low resonance frequency leads to unwanted static deflections of the actuator proof-mass. The use of integral displacement feedback as a local loop within the actuator provides self-levelling capabilities for the inertial actuator proof-mass, thus overcoming the static deflection problem. A novel device for active vibration control, based on an inertial actuator with displacement sensor and local PID controller, is described and its performance is demonstrated experimentally. It is found that the natural frequency and damping of the actuator can also be changed substantially with such a controller, thus allowing an inertial actuator to be customised for a specific application. A frequency-domain formulation is then used to analyse the stability and performance of an active isolation system using the modified inertial actuator and an outer velocity feedback control loop. The plant response, from force actuator input to sensor output, is derived in terms of the mechanical mobilities of the equipment structure being isolated and the vibrating base structure, and the mechanical impedance of the intervening mount. The results of an experimental study of active vibration isolation using a modified inertial actuator are then described. Theory and experiments agree well, demonstrating the effectiveness of the modified inertial actuator.

Fuzzy control of robot manipulators:: some issues on design and rule base size reduction

This paper is aimed at looking into the automatic design and the size reduction of the rule base of fuzzy logic controllers. The first part is concerned with an automatic generation method of the fuzzy rule base. This is done by the use of an intelligent optimization method, and its implementation to the design of a fuzzy controller for robot manipulators. It is assumed that such system is known but ill-defined because of the inherent uncertainties associated with the model. Thus, an accurate mathematical model is not required, but a simplified one is acceptable. The second part treats the reduction of large scale fuzzy rule bases. Two approaches are used for this purpose: the boolean method and the decoupling approach giving a local control loop yielding smaller fuzzy controllers. The boolean approach is based on the equivalence between fuzzy preconditions and on boolean expressions. Using the fact that fuzzy sets are a generalization of classical subsets, we introduced some operations on fuzzy sets that are equivalent to those applied in the boolean logic approach. The paper then discusses the reduction of large scale fuzzy rule bases by the use of a decoupling approach, and its application to the case of an optimal fuzzy logic controller of a three-links robot manipulator using local PID controllers.

IMPLEMENTATION OF CONSTRAINED PREDICTIVE OUTER-LOOP CONTROLLERS: APPLICATION TO A BOILER CONTROL SYSTEM

This paper addresses the problem of implementing predictive controllers for supervisory level control systems. In this configuration the manipulated variables calculated by the Predictive Controller are used as command signals for the Distributed Control Systems, which provide references to the operator-tuned local PID controllers that act on the physical system. This structure introduces the problem of loosing of performance if the inner-loop controllers are re-tuned. The paper discusses the solution to this problem based on the use of a two-degrees-of-freedom structure in the inner loop, that separates open and closed-loop properties. Both design guidelines and robustness issues are discussed.