Coordinated semi-adaptive closed-loop control for infusion of two interacting medications

This paper presents a coordinated and semi‐adaptive closed‐loop control approach to the infusion of 2 interacting medications. The proposed approach consists of an upper‐level coordination controller and a lower‐level semi‐adaptive controller. The coordination controller recursively adjusts the reference targets based on the estimated dose‐response relationship of a patient to ensure that they can be achieved by the patient. The semi‐adaptive controller drives the patient outputs to the reference targets while estimating the patient's dose‐response relationship online. In this way, the controller is resilient to unachievable caregiver‐specified reference targets and responsive to the medication needs of individual patients. To establish the proposed approach, we developed the following: (1) a linear two‐input–two‐output dose‐response model; (2) a two‐input–two‐output semi‐adaptive controller to regulate the patient outputs while adapting high‐sensitivity parameters in the patient model; and (3) a coordination controller to adjust the reference targets that reconcile caregiver inputs and medication use. The proposed approach was applied to an example scenario in which cardiac output and respiratory rate are regulated via infusion of propofol and remifentanil in an in silico simulation setting. The results show that the coordinated semi‐adaptive control could (1) track achievable reference targets with consistent transient and steady‐state performance and (2) resiliently adjust the unachievable reference targets to achievable ones

Intelligent Control Strategies for an Autonomous Underwater Vehicle

The dynamic characteristics of autonomous underwater vehicles (AUVs) present a control problem that classical methods cannot often accommodate easily. Fundamentally, AUV dynamics are highly non-linear, and the relative similarity between the linear and angular velocities about each degree of freedom means that control schemes employed within other flight vehicles are not always applicable. In such instances, intelligent control strategies offer a more sophisticated approach to the design of the control algorithm. Neurofuzzy control is one such technique, which fuses the beneficial properties of neural networks and fuzzy logic in a hybrid control architecture. Such an approach is highly suited to development of an autopilot for an AUV. Specifically, the adaptive network-based fuzzy inference system (ANFIS) is discussed in Chapter 4 as an effective new approach for neurally tuning course-changing fuzzy autopilots. However, the limitation of this technique is that it cannot be used for developing multivariable fuzzy structures. Consequently, the co-active ANFIS (CANFIS) architecture is developed and employed as a novel multi variable AUV autopilot within Chapter 5, whereby simultaneous control of the AUV yaw and roll channels is achieved. Moreover, this structure is flexible in that it is extended in Chapter 6 to perform on-line control of the AUV leading to a novel autopilot design that can accommodate changing vehicle pay loads and environmental disturbances. Whilst the typical ANFIS and CANFIS structures prove effective for AUV control system design, the well known properties of radial basis function networks (RBFN) offer a more flexible controller architecture. Chapter 7 presents a new approach to fuzzy modelling and employs both ANFIS and CANFIS structures with non-linear consequent functions of composite Gaussian form. This merger of CANFIS and a RBFN lends itself naturally to tuning with an extended form of the hybrid learning rule, and provides a very effective approach to intelligent controller development.The Sea Systems and Platform Integration Sector, Defence Evaluation and Research Agency, Winfrit

Analysis and robust decentralized control of power systems using FACTS devices

Today\u27s changing electric power systems create a growing need for flexible, reliable, fast responding, and accurate answers to questions of analysis, simulation, and design in the fields of electric power generation, transmission, distribution, and consumption. The Flexible Alternating Current Transmission Systems (FACTS) technology program utilizes power electronics components to replace conventional mechanical elements yielding increased flexibility in controlling the electric power system. Benefits include decreased response times and improved overall dynamic system behavior. FACTS devices allow the design of new control strategies, e.g., independent control of active and reactive power flows, which were not realizable a decade ago. However, FACTS components also create uncertainties. Besides the choice of the FACTS devices available, decisions concerning the location, rating, and operating scheme must be made. All of them require reliable numerical tools with appropriate stability, accuracy, and validity of results. This dissertation develops methods to model and control electric power systems including FACTS devices on the transmission level as well as the application of the software tools created to simulate, analyze, and improve the transient stability of electric power systems.;The Power Analysis Toolbox (PAT) developed is embedded in the MATLAB/Simulink environment. The toolbox provides numerous models for the different components of a power system and utilizes an advanced data structure that not only increases data organization and transparency but also simplifies the efforts necessary to incorporate new elements. The functions provided facilitate the computation of steady-state solutions and perform steady-state voltage stability analysis, nonlinear dynamic studies, as well as linearization around a chosen operating point.;Applying intelligent control design in the form of a fuzzy power system damping scheme applied to the Unified Power Flow Controller (UPFC) is proposed. Supplementary damping signals are generated based on local active power flow measurements guaranteeing feasibility. The effectiveness of this controller for longitudinal power systems under dynamic conditions is shown using a Two Area - Four Machine system. When large disturbances are applied, simulation results show that this design can enhance power system operation and damping characteristics. Investigations of meshed power systems such as the New England - New York power system are performed to gain further insight into adverse controller effects

A fluid power application of alternative robust control strategies

This thesis presents alternative methods for designing a speed controller for a hydrostatic power transmission system. Recognising that such a system, comprising a valve controlled motor supplied by the laboratory ring main and driving a hydraulic pump as a load, contains significant non-linearities, the thesis shows that robust 'modern control' approaches may be applied to produce viable controllers without recourse to the use of a detailed model of the system. In its introduction, it considers why similar approaches to the design of fluid power systems have not been applied hitherto. It then sets out the design and test, in simulation and on a physical rig, of two alternative linear controllers using H∞ based methods and a 'self organising fuzzy logic' controller (SOFLC). In the linear approaches, differences between the characteristics of the system and the simple models of it are accommodated in the controller design route as 'perturbations' or 'uncertainties'. The H∞ based optimisation methods allow these to be recognised in the design. “Mixed sensitivity” and “Loop shaping” methods are each applied to design controllers which are tested successfully on the laboratory rig. The SOFLC in operation does not rely on a model, but instead allows fuzzy control rules to evolve. In the practical tests, the system is subjected to a range of disturbances in the form of supply pressure fluctuations and load torque changes. Also presented are test results for proportional and proportional plus integral (PI) controllers, to provide a reference. It is demonstrated qualitatively that performance using the linear controllers is superior to that using proportional and PI controllers. An increased range of stable operation is achieved by the controller designed using “loop shaping” – performance is enhanced by the use of two controllers selected automatically according to the operating speed, using a “bumpless” transfer routine. The SOFLC proved difficult to tune. However, stable operation was achieved.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Design of a wireless intelligent fuzzy controller network

Since the first application of fuzzy logic in the field of control engineering, fuzzy logic control has been successfully employed in controlling a wide variety of applications, such as commercial appliances, industrial automation, robots, traffic control, cement kilns and automotive engineering. The human knowledge on controlling complex and non-linear processes can be incorporated into a controller in the form of linguistic expressions. Despite these achievements, however, there is still a lack of an empirical or analytical design study which adequately addresses a systematic auto-tuning method. Indeed, tuning is one of the most crucial parts in the overall design of fuzzy logic controllers and it has become an active research field. Various techniques have been utilised to develop algorithms to fine-tune the controller parameters from a trial and error method to very advanced optimisation techniques. The structure of fuzzy logic controllers is not straightforward as is the case in PID controllers. In addition, there is also a set of parameters that can be adjusted, and it is not always easy to find the relationship between the parameters and the controller performance measures. Moreover, in general, controllers have a wide range of setpoints; changing from one value to another requiring the controller parameters to be re-tuned in order to maintain a satisfactory performance over the entire range of setpoints. This thesis deals with the design and implementation of a new intelligent algorithm for fuzzy logic controllers in a wireless network structure. The algorithm enables the controllers to learn about their plants and systematically tune their gains. The algorithm also provides the capability of retaining the knowledge acquired during the tuning process. Furthermore, this knowledge is shared on the network through a wireless communication link with other controllers. Based on the relationships between controller gains and the closed-loop characteristics, an auto-tuning algorithm is developed. Simulation experiments using standard second order systems demonstrate the effectiveness of the algorithm with respect to auto-tuning, tracking setpoints and rejecting external disturbances. Furthermore, a zero overshoot response is produced with improvements in the transient and the steady state responses. The wireless network structure is implemented using LabVIEW by composing a network of several fuzzy controllers. The results demonstrate that the controllers are able to retain and share the knowledge

Design and Control of Power Converters 2019

In this book, 20 papers focused on different fields of power electronics are gathered. Approximately half of the papers are focused on different control issues and techniques, ranging from the computer-aided design of digital compensators to more specific approaches such as fuzzy or sliding control techniques. The rest of the papers are focused on the design of novel topologies. The fields in which these controls and topologies are applied are varied: MMCs, photovoltaic systems, supercapacitors and traction systems, LEDs, wireless power transfer, etc

Robust Observers And Controllers For Marine Surface Vessels Undergoing Maneuvering And Course-Keeping Tasks

The dynamic behavior of marine surface vessels is highly nonlinear. Moreover, it is significantly influenced by environmental disturbances induced by winds, random sea waves and currents. To yield a desired response of the ship, the guidance and control system of the ship should be robust to both modeling imprecision and significant environmental disturbances. The focus of the current work is threefold. First, a six degree-of-freedom nonlinear model for a marine surface vessel is developed. It accounts for the coriolis and centripetal acceleration terms, added mass and wave damping terms, wave excitation forces, so-called memory effect terms, nonlinear restoring forces, wind and current effects, and control forces and moments. In addition, the formulation accounts for the physical limitations of the rudder and the powertrain system of the ship. In the current work, the detailed model of the vessel is used as a test bed to assess the performances of the proposed guidance system, controllers, and observers under various environmental conditions. A robust sliding mode controller and a self-tuning fuzzy sliding mode controller have been designed in the current work and proven to yield the desired response of the ship through digital simulations. Furthermore, a new guidance system has also been designed based on the line-of-sight and the acceptance radius concepts. The integration of the guidance system with the controllers has led to the design of a fully-autonomous surface vessel that is capable of accurately tracking a specified trajectory without any interference from the person at the helm. Moreover, nonlinear robust observers are designed, based on the sliding mode methodology and the self-tuning fuzzy sliding mode, to yield accurate estimates of the state variables that are needed for the computation of the control actions. The observers play a central role in the integrated guidance and control system proposed for the ship

AUTOMATED MEDICATION INFUSION SYSTEM DESIGN

Automated infusion of medications will be increasingly deployed in patient care as a means to deliver high-quality and continuous monitoring and therapy, and also to alleviate the excessive workload imposed on the clinicians. Therefore, a well-designed automated medication infusion system is an attractive alternative to today’s manual treatment requiring caregiver’s interventions. However, it also presents numerous challenges: 1) Significant inter- and intra-patient variability; 2) Complexity of medication infusion model; 3) Complexity of interaction of multiple medications; 4) Difficulty in coordination of medical targets. So the following approaches are proposed to address the various challenges: First, to deal with the large degree of individual patient variability, an adaptive controller was designed. This is because robust controllers which have fixed parameters might be difficult to offer decent behavior for all patients. Secondly, since classical adaptive controllers can only be applied to linearly parametrized models while even the infusion model of single drug is highly nonlinear and complex, a single-input single-output (SISO) semi-adaptive control approach which only adapt can adapt model parameters having a large impact on the model’s fidelity was introduced. Thirdly, the complicated interaction of multiple medications makes the adaptive controller for two medications even more difficult to design. So a model for two interacting dose responses was constructed and linearized at one operation point. Then the SISO semi-adaptive controller was extended to a two-input two-output case. However, this controller is only designed at one operating point. Therefore, based on two models associated with two distinct operating regimes, a two-model switching control technique was developed and combined with the semi-adaptive controller. Fourthly, we presented a coordinate mechanism to deal with the medical targets setting problem. In real clinical scenarios, the reference targets are empirically specified by caregivers, which are not always achievable in all patients. Therefore, our proposed coordinate mechanism can recursively adjusts the reference targets based on the estimated dose-response relationship of a patient. Lastly, we conducted some SISO control experiments on animals. Based on the experiments, we made some further improvements to the proposed controller