On the Application of Different Event-Based Sampling Strategies to the Control of a Simple Industrial Process

This paper is an experimental study of the utilization of different event-based strategies for the automatic control of a simple but very representative industrial process: the level control of a tank. In an event-based control approach it is the triggering of a specific event, and not the time, that instructs the sensor to send the current state of the process to the controller, and the controller to compute a new control action and send it to the actuator. In the document, five control strategies based on different event-based sampling techniques are described, compared, and contrasted with a classical time-based control approach and a hybrid one. The common denominator in the time, the hybrid, and the event-based control approaches is the controller: a proportional-integral algorithm with adaptations depending on the selected control approach. To compare and contrast each one of the hybrid and the pure event-based control algorithms with the time-based counterpart, the two tasks that a control strategy must achieve (set-point following and disturbance rejection) are independently analyzed. The experimental study provides new proof concerning the ability of event-based control strategies to minimize the data exchange among the control agents (sensors, controllers, actuators) when an error-free control of the process is not a hard requirement

스티어 바이 와이어 시스템의 목표 조향감 재현을 위한 조향 반력 제어

학위논문(박사)--서울대학교 대학원 :공과대학 기계공학부,2020. 2. 이경수.This dissertation focused on the development of and steering assist torque control algorithm of Electric-Power-Steering (EPS) system from the conventional steering system perspective and Steer-by-Wire (SBW) system. The steering assist torque control algorithm has been developed to overcome the major disadvantage of the conventional method of time-consuming tuning to achieve the desired steering feel. A reference steering wheel torque map was designed by post-processing data obtained from target performance vehicle tests with a highly-rated steering feel for both sinusoidal and transition steering inputs. Adaptive sliding-mode control was adopted to ensure robustness against uncertainty in the steering system, and the equivalent moment of inertia damping coefficient and effective compliance were adapted to improve tracking performance. Effective compliance played a role in compensating the error between the nominal rack force and the actual rack force. For the SBW system, the previously proposed EPS assist torque algorithm has been also enhanced using impedance model and applied to steering feedback system. Stable execution and how to give the person the proper steering feedback torque of contact tasks by steering wheel system interaction with human has been identified as one of the major challenges in SBW system. Thus, the problem was solved by utilizing the target steering torque map proposed above. The impedance control consists of impedance model (Reference model with the target steering wheel torque map) and controller (Adaptive sliding mode control). The performance of the proposed controller was evaluated by conducting computer simulations and a hardware-in-the-loop simulation (HILS) under various steering conditions. Optimal steering wheel torque tracking performances were successfully achieved by the proposed EPS and SBW control algorithm.본 논문은 종래의 조향 시스템 관점에서 전동식 동력 조향 (EPS) 시스템과 스티어 바이 와이어 (SBW) 조향 보조 토크 제어 알고리즘의 개발을 중점으로 하였습니다. 기존 조향 보조 토크 제어 알고리즘은 원하는 조향감을 구현하기 위해 종래의 시간 소모적 인 튜닝 방법을 사용합니다. 이러한 주요 단점을 극복하기 위해 새로운 조향 보조 제어 알고리즘을 개발하였습니다. 목표 스티어링 휠 토크 맵은 정현파(Weave test) 및 등속도 스티어링 입력 (Transition test) 모두에 대해 높은 등급의 조향감을 차량 테스트에서 얻은 후 데이터 처리를 하여 설계되었습니다. 스티어링 시스템의 불확실성에 대한 강건성을 보장하기 위해 적응 형 슬라이딩 모드 제어가 채택되었으며, 관성 모멘트 감쇠 계수와 컴플라이언스 계수(Effective compliance)가 제어기 성능을 개선하도록 적응형 파라미터로 선정되었습니다. 컴플라이언스 계수는 계산된 랙 힘과 실제 랙 힘 사이의 차이를 보상하는 역할을 했습니다. SBW 시스템의 경우, 이전에 제안 된 EPS 지원 토크 알고리즘을 개선하고 향상시키기 위해 임피던스 모델을 사용하였으며 스티어링 피드백 시스템에 적용되었습니다. SBW 시스템의 주요 과제 중 하나는 사람과 스티어링 휠 시스템 상호 작용에 의해 안정적인 작동과 사람에게 적절한 스티어링 피드백 토크를 제공하는 방법입니다. 임피던스 제어는 임피던스 모델 (타겟 스티어링 휠 토크 맵)과 컨트롤러 (적응 슬라이딩 모드 제어)로 구성됩니다. 따라서, 상기 제안 된 목표 조향 토크 맵을 이용함으로써 스티어 바이 와이어에서 스티어링 피드백 토크를 절절히 적용 됨을 확인 하였습니다. 제안 된 컨트롤러의 성능은 다양한 조향 조건에서 컴퓨터 시뮬레이션 및 HILS (Hardware-in-the-loop) 시뮬레이션을 수행하여 평가되었습니다. 제안 된 EPS 및 SBW 제어 알고리즘을 통해 최적의 스티어링 휠 토크 추적 성능을 달성했습니다.Chapter 1 Introduction 1 1.1. Background and Motivation 1 1.2. Previous Researches 4 1.3. Thesis Objectives 9 1.4. Thesis Outline 10 Chapter 2 Dynamic Model of Steering Systems 11 2.1. Dynamic model of Hydraulic/Electrohydraulic Power-Assisted Steering Model 11 2.2. Dynamic model of Electric-Power-Assisted-Steering Model 17 2.3. Dynamic model of Steer-by-Wire Model 21 2.4. Rack force characteristic of steering system 23 Chapter 3 Target steering wheel torque tracking control 28 3.1. Target steering torque map generation 28 3.2. Adaptive sliding mode control design for target steering wheel torque tracking with EPS 30 3.2.1. Steering states estimation with a kalman filter 38 3.3. Impedance Control Design for Target Steering Wheel Torque Tracking with SBW 43 Chapter 4 Validation with Simulation and Hardware-in-the-Loops Simulation 49 4.1. Computer Simulation Results for EPS system 49 4.2. Hardware-in-the-Loops Simulation Results for EPS system 61 4.3. Computer Simulation Results for SBW system 77 4.4. Hardware-in-the-Loops Simulation Results for SBW system 82 Chapter 5 Conclusion and Future works 89 Bibliography 91 Abstract in Korean 97Docto

Shared Control Policies and Task Learning for Hydraulic Earth-Moving Machinery

This thesis develops a shared control design framework for improving operator efficiency and performance on hydraulic excavation tasks. The framework is based on blended shared control (BSC), a technique whereby the operator’s command input is continually augmented by an assistive controller. Designing a BSC control scheme is subdivided here into four key components. Task learning utilizes nonparametric inverse reinforcement learning to identify the underlying goal structure of a task as a sequence of subgoals directly from the demonstration data of an experienced operator. These subgoals may be distinct points in the actuator space or distributions overthe space, from which the operator draws a subgoal location during the task. The remaining three steps are executed on-line during each update of the BSC controller. In real-time, the subgoal prediction step involves utilizing the subgoal decomposition from the learning process in order to predict the current subgoal of the operator. Novel deterministic and probabilistic prediction methods are developed and evaluated for their ease of implementation and performance against manually labeled trial data. The control generation component involves computing polynomial trajectories to the predicted subgoal location or mean of the subgoal distribution, and computing a control input which tracks those trajectories. Finally, the blending law synthesizes both inputs through a weighted averaging of the human and control input, using a blending parameter which can be static or dynamic. In the latter case, mapping probabilistic quantities such as the maximum a posteriori probability or statistical entropy to the value of the dynamic blending parameter may yield a more intelligent control assistance, scaling the intervention according to the confidence of the prediction. A reduced-scale (1/12) fully hydraulic excavator model was instrumented for BSC experimentation, equipped with absolute position feedback of each hydraulic actuator. Experiments were conducted using a standard operator control interface and a common earthmoving task: loading a truck from a pile. Under BSC, operators experienced an 18% improvement in mean digging efficiency, defined as mass of material moved per cycle time. Effects of BSC vary with regard to pure cycle time, although most operators experienced a reduced mean cycle time

A cable-suspended intelligent crane assist device for the intuitive manipulation of large payloads

This paper presents a cable-suspended crane system to assist operators in moving and lifting large payloads. The main objective of this work is to develop a simple and reliable system to help operators in industry to be more productive while preventing injuries. The system is based on the development of a precise and reliable cable angle sensor and a complete dynamic model of the system. Adaptive horizontal and vertical controllers designed for direct physical human-robot interaction are then proposed. Different techniques are then proposed to estimate the payload acceleration in order to increase the controller performances. Finally, experiments performed on a full-scale industrial system are presented

Heat pump controls to exploit the energy flexibility of building thermal loads

Smart controls for heat pumps are required to harness the full energy flexibility potential of building thermal loads. A literature review revealed that most strategies used for this purpose can be classified in two categories: simpler rule-based control (RBC), and model predictive control (MPC), a more complex strategy based on optimization and requiring a prior model of the systems. Both RBC and MPC can use external penalty signals to prompt their actions. The price of electricity is most often used for this purpose, leading to strategies of cost reduction. As an alternative penalty signal, a novel marginal CO2 emissions signals was also conceived. In this thesis, both an RBC and an MPC controllers were developed as supervisory controls for an air-to-water heat pump supplying the heating and cooling needs of a residential building type from the Mediterranean area of Spain. The RBC strategy modulates the temperature set-points, while the MPC strategy minimizes the overall summed penalties (costs or emissions) due to the heat pump use, while balancing with comfort constraints and a proper operation of the systems. The MPC controller in particular required the development of a simplified model of the building envelope and of the heat pump performance, both adjusted differently for heating or cooling. The MPC included several novelties, such as the mixed-integer formulation, the heat pump simplified model based on experimental data and the consideration of its computational delay. The developed controllers were then tested, firstly in an experimental “hardware-in-the-loop” setup, with a real heat pump installed in the laboratory facilities, and connected to thermal benches that emulated the loads from a building model. Implementing the control strategies on a real heat pump enabled to highlight some practical challenges such as model mismatch in the MPC, communication issues, interfacing and control conflicts with the heat pump local controller. Secondly, a simulation-only framework was developed to test other configurations of the controllers, with TRNSYS as the main dynamic building simulation tool, coupled with MATLAB for the MPC controller. In that case, the real heat pump was replaced by a detailed model which was specially developed for this purpose. It is based on static tests performed in the laboratory, and therefore reproduces the dynamic behavior of the heat pump with high fidelity. The results from experimental and simulation studies revealed the ability of both types of controllers to shift the building loads towards periods of cheaper or less CO2-emitting electricity, these two objectives being in fact contradictory. In the cases where the reference control presented a large margin for improvements, the RBC and MPC controllers performed equally and provided important savings: around 15% emissions savings in heating mode, and 30% cost savings in cooling mode. In the cases where the reference control already performed close to optimally, the RBC controller failed to provide improvements, while the MPC benefitted from its stronger optimization and prediction features, reaching 5% cost savings in heating mode and 10% emissions savings in cooling mode. The research carried out in this thesis covered many aspects of energy flexibility in buildings: creation of input penalty signals, graphical representation of flexibility, development of controllers, performance in realistic experimental setup, fitting of appropriate models and compared performance in heating and cooling. The development efforts and barriers hindering the deployment of MPC controllers at large scale for building climate control have additionally been discussed. The performance of the developed controllers was evidenced in the thesis, proving their potential for load-shifting incentivized by different penalty signals: they could become a strong asset to unlock demand-side flexibility and in fine, help integrating a larger share of RES in the grid.Para aprovechar todo el potencial de flexibilidad energética de las cargas térmicas en los edificios equipados con bombas de calor se requiere de sistemas de control inteligente. Una revisión bibliográfica ha revelado que la mayoría de las estrategias de gestión utilizadas para esta finalidad pueden ser clasificadas en dos categorías: control en base a reglas (RBC en inglés) o predictivo (MPC en inglés), basado en optimización y en el uso de modelos. Tanto RBC como MPC pueden utilizar señales externas de penalización para fundamentar sus decisiones. El precio de la electricidad es utilizado a este fin de forma habitual en estrategias de reducción de coste. Una nueva señal de emisiones marginales de CO2 fue también creada como alternativa. Se han desarrollado un controlador RBC y un MPC para sistemas de bombas de calor aire-agua que cubren las demandas de climatización y agua caliente en el ámbito residencial. El RBC modula las consignas de temperatura, y el MPC minimiza las penalizaciones totales del sistema, al mismo tiempo que se consideran restricciones operativas y de confort. En particular, el MPC ha requerido el desarrollo de nuevos modelos simplificados, para predecir la demanda del edificio y el rendimiento de la bomba de calor, tanto en modo calefacción como en modo refrigeración. Otras novedades añadidas en la configuración del MPC son la formulación entera mixta, y la consideración del retraso debido al tiempo de cómputo. Los controladores fueron testeados, primeramente, en un entorno experimental -hardware-in-the-loop-, con una bomba de calor real instalada en el laboratorio y conectada a unos bancos térmicos que emulan las cargas térmicas del edificio. El entorno experimental ha permitido poner de manifiesto algunos retos prácticos tales como la discrepancia en el modelo del MPC y conflictos de conexión con el controlador local de la bomba de calor. En segundo lugar, un entorno de simulación ha sido creado para testear diversas configuraciones, usando TRNSYS acoplado con MATLAB. Para ello, se ha desarrollado un modelo detallado de la bomba de calor, basado en ensayos realizados en laboratorio, que reproduce el comportamiento dinámico de la bomba de calor con alta fidelidad. Tanto los resultados experimentales como los simulados han revelado la capacidad de los dos tipos de control de desplazar las cargas del edificio hacia periodos donde la electricidad era más barata o había menos emisiones de CO2, estos dos objetivos presentando de hecho impactos contradictorios. En los casos donde el control de referencia presentaba un amplio margen de mejora, los controladores RBC y MPC han demostrado la capacidad de actuar eficientemente y proveer ahorros importantes: alrededor de un 15% de emisiones en modo calefacción, y de un 30% de coste en modo frío. En aquellos casos en el que el control de referencia actuaba de forma cercana a la óptima, los controladores RBC no han sido capaces de aportar mejoras significativas, mientras que el MPC ha demostrado la capacidad de conseguir ahorros de un 5% de coste en modo calefacción y de un 10% de emisiones en modo frío. La investigación realizada en esta tesis ha abarcado amplios aspectos de la flexibilidad energética en los edificios: la generación de señales de penalización, la representación gráfica del potencial de flexibilidad, el ajuste de modelos simplificados, el desarrollo de controladores, el ensayo en entorno experimental y de simulación, con la consecuente evaluación de su rendimiento comparado en periodos de invierno y de verano, así como una discusión de las barreras que dificultan la implementación de controladores MPC y RBC a gran escala. Finalmente, la tesis ha evidenciado el rendimiento de los controladores desarrollados si se formulan de forma adecuada, demostrando su potencial para el desplazamiento del consumo eléctrico en la edificación residencial con sistemas de bomba de calor respondiendo a diferentes señales de penalización. En conclusión, los sistemas propuestos pueden ser elementos muy valiosos para favorecer la necesaria flexibilidad de la demanda térmica en la edificación y posibilitar la integración de sistemas de generación renovables en la re

Root cause isolation of propagated oscillations in process plants

Persistent whole-plant disturbances can have an especially large impact on product quality and running costs. There is thus a motivation for the automated detection of a plant-wide disturbance and for the isolation of its sources. Oscillations increase variability and can prevent a plant from operating close to optimal constraints. They can also camouflage other behaviour that may need attention such as upsets due to external disturbances. A large petrochemical plant may have a 1000 or more control loops and indicators, so a key requirement of an industrial control engineer is for an automated means to detect and isolate the root cause of these oscillations so that maintenance effort can be directed efficiently. The propagation model that is proposed is represented by a log-ratio plot, which is shown to be ‘bell’ shaped in most industrial situations. Theoretical and practical issues are addressed to derive guidelines for determining the cut-off frequencies of the ‘bell’ from data sets requiring little knowledge of the plant schematic and controller settings. The alternative method for isolation is based on the bispectrum and makes explicit use of this model representation. A comparison is then made with other techniques. These techniques include nonlinear time series analysis tools like Correlation dimension and maximal Lyapunov Exponent and a new interpretation of the Spectral ICA method, which is proposed to accommodate our revised understanding of harmonic propagation. Both simulated and real plant data are used to test the proposed approaches. Results demonstrate and compare their ability to detect and isolate the root cause of whole plant oscillations. Being based on higher order statistics (HOS), the bispectrum also provides a means to detect nonlinearity when oscillatory measurement records exist in process systems. Its comparison with previous HOS based nonlinearity detection method is made and the bispectrum-based is preferred

Model predictive control design for multivariable processes in the presence of valve stiction

This paper presents different formulations of Model Predictive Control (MPC) to handle static friction in control valves for industrial processes. A fully unaware formulation, a stiction embedding structure, and a stiction inversion controller are considered. These controllers are applied to multivariable systems, with linear and nonlinear process dynamics. A semiphysical model is used for valve stiction dynamics and the corresponding inverse model is derived and used within the stiction inversion controller. The two-move stiction compensation method is revised and used as warm-start to build a feasible trajectory for the MPC optimal control problem. Some appropriate choices of objective functions and constraints are used with the aim of improving performance in set-points tracking. The different MPC formulations are reviewed, compared, and tested on several simulation examples. Stiction embedding MPC proves to guarantee good performance in set-points tracking and also stiction compensation, at the expense of a lower robustness with respect to other two formulations