Control Performance Evaluation Research Articles

Implementation of power‐aided control for a virtual reality exercise bike

This paper investigates the designs and applications of a virtual reality exercise bike system utilizing active power control. An impedance control which employs a state filter to simplify certain circuits such as torque sensors, is presented for executing functions required by these machines. This approach can be used to improve the indoor exercise experience and assist in physical rehabilitation. Moreover, this method, as opposed to passive techniques, gives patients more options in their endeavors to recover. An experimental setup is given to evaluate control performance in real time and also to demonstrate some practical uses.

분산 실시간 제어 시스템을 위한 TTP 네트워크 시스템의 구현

Recently, many ECUs(Electronic Control Units) have been used to enhance the vehicle safety, which leads to a distributed real-time control system. The distributed real-time control system requires to reduce the network delay for dependable real-time performance. There are two different paradigms by which a network protocol operates: event-triggered and time-triggered. This paper focuses on implementation of a time-triggered protocol. i.e. TTP/C(Time-Triggered Protocol/class C). This paper presents a design method of TTP control network and performance evaluation of distributed real-time control system using TTP protocol.

Experimental implementation of a building structure with a tuned liquid column damper based on the real-time hybrid testing method

In this study, the real-time hybrid test using a shaking table for the control performance evaluation of a U-shaped tuned liquid column damper (TLCD) controlling the response of earthquake-excited building structure is experimenttally implemented. In the test, the building structure is used as a numerical part, on which a U-shaped TLCD adopted as an experimental part was installed to reduce its response. At first, the force that is acting between a TLCD and building structure is measured from the load cell attached on shaking table and is fed-back to the computer to control the motion of shaking table. Then, the shaking table is driven such a manner that the error between the interface acceleration computed from the numerical building structure under the excitations of earthquake and the fed-back interface force and that measured from the shaking table. The control efficiency of the TLCD used in this paper is experimentally confirmed by implementing this process of shaking table experiment on real-time.

ファジィ制御による自動着陸の制御則

The effectiveness of fuzzy logic control law for automatic landing of aircraft, which cover both of control to lead aircraft from level flight at an altitude of 500m to the flight on the glide-path course near the runway and control for the aircraft to land smoothly on a runway, was studied. The control law of the automatic landing was designed to match the design goals of leading from the horizontal flight to the flight on the glide-path course quickly and smoothly and of landing smoothly on a runway. Because there is the ground effect at landing, design of control law and evaluation of control performance were done in consideration of the ground effect. As a result, it was confirmed that the design objective was achieved. Even if the characteristics of the plant changes greatly, this control law was able to maintain the control performance. Moreover, it was confirmed to be able to land safely when there was air turbulence. This paper shows that fuzzy logic control is an effective and flexible method when applied to control law for automatic landing and the design method of control law using fuzzy logic control was obtained.

A low‐order model for analysing effects of blade fatigue load control

AbstractA new low‐order mathematical model is introduced to analyse blade dynamics and blade load‐reducing control strategies for wind turbines. The model consists of a typical wing section model combined with a rotor speed model, leading to four structural degrees of freedom (flapwise, edgewise and torsional blade oscillations and rotor speed). The aerodynamics is described by an unsteady aerodynamic model. The equations of motion are derived in non‐linear and linear form. The linear equations of motion are used for stability analysis and control design. The non‐linear equations of motion are used for time simulations to evaluate control performance. The stability analysis shows that the model is capable of predicting classical flutter and stall‐induced vibrations. The results from the stability analysis are compared with known results, showing good agreement. The model is used to compare the performance of one proportional–integral–derivative controller and two full‐state feedback controllers. Copyright © 2006 John Wiley & Sons, Ltd.

Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers

Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design parameters. The objective is to examine the amount by which the extra degrees of freedom provided by antecedent type-2 fuzzy sets is able to improve the control performance. Experimental results show that better control can be achieved using a type-2 FLC with fewer fuzzy sets/rules so one benefit of type-2 FLC is a lower trade-off between modeling accuracy and interpretability.

Towards a benchmark simulation model for plant-wide control strategy performance evaluation of WWTPs

The COST/IWA benchmark simulation model has been available for seven years. Its primary purpose has been to create a platform for control strategy benchmarking of activated sludge processes. The fact that the benchmark has resulted in more than 100 publications, not only in Europe but also worldwide, demonstrates the interest in such a tool within the research community In this paper, an extension of the benchmark simulation model no 1 (BSM1) is proposed. This extension aims at facilitating control strategy development and performance evaluation at a plant-wide level and, consequently, includes both pre-treatment of wastewater as well as the processes describing sludge treatment. The motivation for the extension is the increasing interest and need to operate and control wastewater treatment systems not only at an individual process level but also on a plant-wide basis. To facilitate the changes, the evaluation period has been extended to one year. A prolonged evaluation period allows for long-term control strategies to be assessed and enables the use of control handles that cannot be evaluated in a realistic fashion in the one-week BSM1 evaluation period. In the paper, the extended plant layout is proposed and the new suggested process models are described briefly. Models for influent file design, the benchmarking procedure and the evaluation criteria are also discussed. And finally, some important remaining topics, for which consensus is required, are identified.

05/02079 Coordinated design and performance evaluation of UPFC supplementary modulation controllers

05/02079 Coordinated design and performance evaluation of UPFC supplementary modulation controllers

Self-organizing fuzzy control of constant cutting force in turning

Constant force control is gradually becoming an important technique in the modern manufacturing process. Especially, constant cutting force control is a useful approach in increasing the metal removal rate and the tool life for turning systems. However, turning systems generally have nonlinear with uncertainty dynamic characteristics. Designing a model-based controller for constant cutting force control is difficult because an accurate mathematical model in the turning system is hard to establish. Hence, this study employed a model-free fuzzy controller to control the turning system in order to achieve constant cutting force control. Nevertheless, the design of the traditional fuzzy controller (TFC) presents difficulties in finding control rules and selecting an appropriate membership function. Moreover, the database and fuzzy rules of a TFC are fixed after the design step and then cannot appropriately regulate ones real time according to the system output response and the desired control performance. To solve the above problem, this work develops a self-organizing fuzzy controller (SOFC) for constant cutting force control to evaluate control performance of the turning system. The SOFC continually updates the learning strategy in the form of fuzzy rules, during the turning process. The fuzzy rule table of this SOFC can be begun with zero initial fuzzy rules which not only overcome the difficulty in the TFC design, but also establish a suitable fuzzy rules table, and support practically convenient fuzzy controller applications in turning systems control. To confirm the applicability of the proposed intelligent controllers, this work retrofitted an old lathe for a turning system to evaluate the feasibility of constant cutting force control. The SOFC has a better control performance in constant cutting force control than does the TFC, as verified in experimental results.

An autonomous controller for site-specific management of fixed irrigation systems

Distributed irrigation control (DIC) for site-specific management and/or operation of fixed irrigation systems is easier to install and maintain as compared to centralized irrigation control (CIC), but requires multiple controllers in the field. The advantages of DIC over CIC systems include: (1) reduced wiring and piping requirements, (2) a lower risk of complete system failure due to mechanical damage or lightening strikes, and (3) more flexibility when modifying or extending the system. In this study, a low cost solar-powered feedback controller for DIC of fixed irrigation systems was developed and tested. The specific tasks included the controller design (hardware and software), performance evaluation, and power optimization. The controller uses soil water potential (SWP) measurements to control the amount of water applied to each specific management area of a field, and measured system hydraulic pressure to communicate with other controllers. Each controller is autonomously powered by a solar panel and battery, eliminating hard-wire connections among control units. The results indicate that the controller was effective in maintaining the SWP in the root zone close to a predetermined management allowed deficit (MAD). The power supply was optimized using simulated and measured solar radiation data from two locations.

Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control

Neural networks have recently received a great deal of attention in the field of manufacturing process quality control, where statistical techniques have traditionally been used. In this paper, a neural-based procedure for quality monitoring is discussed from a statistical perspective. The neural network is based on Fuzzy ART, which is exploited for recognising any unnatural change in the state of a manufacturing process. Initially, the neural algorithm is analysed by means of geometrical arguments. Then, in order to evaluate control performances in terms of errors of Types I and II, the effects of three tuneable parameters are examined through a statistical model. Upper bound limits for the error rates are analytically computed, and then numerically illustrated for different combinations of the tuneable parameters. Finally, a criterion for the neural network designing is proposed and validated in a specific test case through simulation. The results demonstrate the effectiveness of the proposed neural-based procedure for manufacturing quality monitoring.

Analysis and performance evaluation of the EFCM common congestion controller for TCP connections

Today’s standard TCP implementations perform congestion control separately for each connection of an end system. It is advantageous in terms of overall performance, e.g., throughput and (short-term) fairness, to share network information between several TCP connections of an end system by establishing a common congestion control. In this paper, we present a new common congestion-control approach called “ensemble flow congestion management” (EFCM). First, we describe the design constraints of EFCM. Then, we explain and analyze the EFCM control algorithms. After that, we investigate the performance improvement of EFCM compared to standard TCP congestion control under different network conditions. Simulations with EFCM show a considerable increase in throughput and (short-term) fairness without increasing the aggressiveness of a set of TCP connections—we also show this analytically using a fairness argument. The proposed EFCM controller algorithms are easy to implement and have a low additional complexity.

Decentralized Flight Control Integration and Performance Evaluation

Decentralized flight control shows great advantage in implementation, and is well fitted into a systematic flight control systems development and engineering process. However, the preservation of locally achieved design specifications under the integrated system environment is largely unknown. This work proposes two control integration approaches to address this challenge. It describes both open-loop and closed-loop integration strategies within an integrated control framework. Furthermore, the selection of candidate subsystems is also taken into account during integration. Using an integrated longitudinal pitch attitude and speed control example, the performance of both strategies is evaluated. Numerical simulation results are included for further demonstration.

Coordinated design and performance evaluation of UPFC supplementary modulation controllers

Mitigation of low-frequency electro-mechanical oscillations is essential for secure operation of power systems. The fast acting, power electronics based FACTS controllers which are capable of improving both steady state and dynamic performance permit newer approaches to system stabilization. The objective of the work presented in this paper is to carry out a coordinated design of supplementary modulation controllers (SMCs) for UPFC and to evaluate their performance. The effectiveness of the SMCs in damping the critical modes is tested on a four machine, 10 bus system.

Towards a common benchmark for long-term process control and monitoring performance evaluation

The COST/IWA benchmark simulation model has been available for seven years. Its primary purpose has been to create a platform for control strategy benchmarking of biological wastewater treatment processes. The fact that the benchmark has resulted in more than 100 publications, not only in Europe but also worldwide, demonstrates the interest for such a tool in the research community. In this paper, an extension of the benchmark simulation model no. 1 (BSM1) is proposed. It aims at facilitating evaluation of two closely related operational tasks: long-term control strategy performance and process monitoring performance. The motivation for the extension is that these two tasks typically act on longer time scales. The extension proposed here consists of 1) prolonging the evaluation period to one year (including influent files), 2) specifying time varying process parameters and 3) including sensor and actuator failures. The prolonged evaluation period is necessary to obtain a relevant and realistic assessment of the effects of such disturbances. Also, a prolonged evaluation period allows for a number of long-term control actions/handles that cannot be evaluated in a realistic fashion in the one week BSM1 evaluation period. In the paper, models for influent file design, parameter changes and sensor failures, initialization procedure and evaluation criteria are discussed. Important remaining topics, for which consensus is required, are identified. The potential of a long-term benchmark is illustrated with an example of process monitoring algorithm benchmarking.

Controller design and performance evaluation for deadlock avoidance in automated flexible manufacturing cells

In this paper, the design of a deadlock avoidance controller is described. The uncontrolled system is modeled using colored Petri nets. The system controller is based on a restrictive (not maximally permissive) deadlock avoidance policy to resolve deadlocks and control the real-time resource allocation decisions in the system. Performance evaluation of systems controlled by not maximally permissive algorithms is essential in determining the applicability and effectiveness of the control algorithms. The performance of the controlled system is compared with performance of optimal control policies to quantify the effects of the restrictiveness of the deadlock avoidance policy on system performance.

On Evaluating Control Performance on Large Data Sets

The evaluation of control performance by means of performance indices from large amounts of measurement data is investigated. The focus is twofold: Firstly to assess information that can be deduced from many data sets and secondly to investigate the usefulness of simple performance measures. Established methods and some useful new ideas are evaluated on many industrial data sets and the results are discussed

Quantitative Evaluation for Skill Controller Based on Comparison With Human Demonstration

One of the promising strategies to design a skill controller for robots is to observe the human worker's skill and embed it in the robot controller under certain control architecture. However, no systematic design strategies to realize this scenario have yet been developed due to the lack of a quantitative performance evaluation of the skill controller. In this brief, the switching-impedance controller is considered as the skill controller and is developed based on a comparison with human worker's demonstration. The enabling condition to switch the impedance parameter is optimized by calculating a hidden Markov model (HMM) distance which can measure the similarity between the skill of the human worker and the robot. HMM is a doubly stochastic system and is recognized as a useful tool for speech recognition. Thanks to the similarity in the stochastic characteristics between speech and skill (position/force) data, HMM is also expected to play a crucial role in skill controller design. An insertion task of deformable objects with the assistance of a vision sensor is considered in this brief. Some parameters which appear in the skill controller are optimized so as to increase the similarity with human worker's demonstration.

Identification and control of an industrial polymerisation reactor

This paper deals with the application of model identification and control to an industrial polymerisation process. The final control objective in the present process is to obtain a polymer of a viscosity as homogeneous as possible. The process has two inputs : the catalyst feed rate and the air flow rate in the reactor. The first input is the control input, and the second is a measured disturbance. The process model is identified from industrial data. The model identification (e.g. System identification-theory for the user. Englewood Cliffs, NJ: Prentice-Hall, 1987; and Model validation and model structure determination. Englewood Cliffs, NJ: Prentice-Hall, 1989.) also accounts for a drift in the gain of the transfer function between the polymer viscosity and the catalyst feed rate. The drift is due to the coating of the reactor with high viscosity polymer. The identified model is used to design a predictive controller with feedforward action of the air flow rate. The controller is tested in numerical simulation. The present study covers all aspects from the model structure and parameter identification to the control design and control performance evaluation.

Development of a Technique for Performance Evaluation of Industrial Controllers

Abstract The paper describes a method to account for different issues of performance monitoring of industrial control systems, under SISO control: detection of poorly tuned loops, process identification, controllers retuning and evaluation of performance improvements. The procedure can be completely automated and applied on-line or offline; it starts from the analysis of plants data and ends up with a suggestion to the operator about the new controller settings. Characteristics and effectiveness of the technique are illustrated by simulations results and application to industrial plant data.