Improving Optical Trap Measurements with Adaptive Nonlinear Control Methods

An optical trap uses radiation pressure of light to manipulate microscopic objects. The interaction between the light and the microscopic objects result in the objects experiencing optical forces. These forces are on the same order of magnitude as biological forces (typically \SIrange[range-units=single]{0.1}{100}{\pico\newton}) and this feature makes optical traps appropriate for single-molecule studies. Currently, there is a growing need to create an automated optical trap that uses the entire operating range of the optical trap to study the biological forces. Spatial nonlinearities in the optical force and parameter uncertainty complicate feedback control for optical traps. A consequence is that users are spending an enormous amount of time calibrating the instrument and designing a controller, and this diverts their time away from studying the biophysics. This research explores the use of nonlinear and adaptive feedback methods to create an automated optical trap. A model is defined to describe the coupling between the dynamics of the optical trap and molecule, and the nominal force within the molecule is treated as a disturbance. The disturbance information is obtained by creating a disturbance model and combining its dynamics with the system dynamics. The system nonlinearities are addressed by using a nonlinear Kalman filter to estimate the system state, then the system state is used in a input-output feedback linearization and linear quadratic structure to satisfy performacne requirements. Statistical analyses are performed to assess the effectiveness the feedback methods have on the open-loop and closed-loop systems. Its performance is compared with that of linear integral control used in practice to quantify the performance improvement when considering the system nonlinearities in the control design. The system nonlinearities and parameter uncertainty are addressed by using adaptive and nonlinear feedback methods. An adaptive state observer provides a simultaneous estimate of the system state and parameters, then these estimated entities are used in an adaptive input-output feedback linearization and LQ structure. The result is the creation of an automated self-tuning optical trap that minimizes the user interaction with the instrument calibration and control design, uses the entire operating range of the optical trap, and obtains an unbiased estimate of the molecule force. The closed-loop performance of these feedback methods are demonstrated by replicating the force-extension curve of a DNA molecule

Thermodynamic analysis, modelling and control of a novel hybrid propulsion system

Stringent emission regulations imposed by governments and depleting fossil fuel reserves have promoted the development of the automotive industry towards novel technologies. Various types of hybrid power plants for transport and stationary applications have emerged. The methodology of design and development of such power plants varies according to power producing components used in the systems. The practical feasibility of such power plants is a pre-requisite to any further development. This work presents thermodynamic analysis and modelling of such a novel power plant, assesses its feasibility and further discusses the development of a suitable control system. The proposed system consists of a hybrid configuration of a solid oxide fuel cell and IC engine as the main power producing components. A reformer supplies fuel gas to the fuel cell while the IC engine is supplied with a liquid fuel. The excess fuel from the fuel cell anode and the oxygen-depleted air from cathode of the fuel cell are also supplied to the engine. This gas mixture is aspirated into the engine with the balance of energy provided by the liquid fuel. The fuel cell exhaust streams are used to condition the fuel in the engine to ensure minimum pollutants and improved engine performance. Both, fuel cell and engine share the load on the system. The fuel cell operates on a base load while the engine handles majority of the transient load. This system is particularly suitable for a delivery truck or a bus cycle. Models of the system components reformer, solid oxide fuel cell, IC engine and turbocharger were developed to understand their steady state and dynamic behaviour. These models were validated against sources of literature and used to predict the effect of different operating conditions for each component. The main control parameters for each component were derived from these models. A first law analysis of the system at steady state was conducted to identify optimum operating region, verify feasibility and efficiency improvement of the system. The results suggested reduced engine fuel consumption and a 10 % improvement in system efficiency over the conventional diesel engines. Further, a second law analysis was conducted to determine the key areas of exergy losses and the rational efficiency of the system at full load operating conditions. The results indicate a rational efficiency of 25.4 % for the system. Sensitivity to changes in internal exergy losses on the system work potential was also determined. The exergy analysis indicates a potential for process optimisation as well as design improvements. This analysis provides a basis for the development of a novel control strategy based on exergy analysis and finite-time thermodynamics. A dynamic simulation of the control oriented system model identified the transient response and control parameters for the system. Based on these results, control systems were developed based on feedback control and model predictive control theories. These controllers mainly focus on air and fuel path management within the system and show an improved transient response for the system. In a hierarchical control structure for the system, the feedback controllers or the model predictive controller can perform local optimisation for the system, while a supervisory controller can perform global optimisation. The objective of the supervisory controller is to determining the load distribution between the fuel cell and the engine. A development strategy for such a top-level supervisory controller for the system is proposed. The hybrid power plant proposed in this thesis shows potential for application for transport and stationary power production with reduced emissions and fuel consumption. The first and second law of thermodynamics can both contribute to the development of a comprehensive control system. This work integrates research areas of powertrain design, thermodynamic analysis and control design. The development and design strategy followed for such a novel hybrid power plant can be useful to assess the potential of other hybrid systems as well

A Model-Based Framework for the Smart Manufacturing of Polymers

It is hard to point a daily activity in which polymeric materials or plastics are not involved. The synthesis of polymers occurs by reacting small molecules together to form, under certain conditions, long molecules. In polymer synthesis, it is mandatory to assure uniformity between batches, high-quality of end-products, efficiency, minimum environmental impact, and safety. It remains as a major challenge the establishment of operational conditions capable of achieving all objectives together. In this dissertation, different model-centric strategies are combined, assessed, and tested for two polymerization systems. The first system is the synthesis of polyacrylamide in aqueous solution using potassium persulfate as initiator in a semi-batch reactor. In this system, the proposed framework integrates nonlinear modelling, dynamic optimization, advanced control, and nonlinear state estimation. The objectives include the achievement of desired polymer characteristics through feedback control and a complete motoring during the reaction. The estimated properties are close to experimental values, and there is a visible noise reduction. A 42% improvement of set point accomplishment in average is observed when comparing feedback control combined with a hybrid discrete-time extended Kalman filter (h-DEKF) and feedback control only. The 4-state geometric observer (GO) with passive structure, another state estimation strategy, shows the best performance. Besides achieving smooth signal processing, the observer improves 52% the estimation of the final molecular weight distribution when compared with the h-DEKF. The second system corresponds to the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst in a semi-batch reactor. The evaluated operating conditions consider different diene concentrations and reaction temperatures. Initially, the nonlinear model is validated followed by a global sensitivity analysis, which permits the selection of the important parameters. Afterwards, the most important kinetic parameters are estimated online using an extended Kalman filter (EKF), a variation of the GO that uses a preconditioner, and a data-driven strategy referred as the retrospective cost model refinement (RCMR) algorithm. The first two strategies improve the measured signal, but fail to predict other properties. The RCMR algorithm demonstrates an adequate estimation of the unknown parameters, and the estimates converge close to theoretical values without requiring prior knowledge

Vibration isolation with smart fluid dampers: a benchmarking study

The non-linear behaviour of electrorheological (ER) and magnetorheological (MR) dampers makes it difficult to design effective control strategies, and as a consequence a wide range of control systems have been proposed in the literature. These previous studies have not always compared the performance to equivalent passive systems, alternative control designs, or idealised active systems. As a result it is often impossible to compare the performance of different smart damper control strategies. This article provides some insight into the relative performance of two MR damper control strategies: on/off control and feedback linearisation. The performance of both strategies is benchmarked against ideal passive, semi-active and fully active damping. The study relies upon a previously developed model of an MR damper, which in this work is validated experimentally under closed-loop conditions with a broadband mechanical excitation. Two vibration isolation case studies are investigated: a single-degree-of-freedom mass-isolator, and a two-degree-of-freedom system that represents a vehicle suspension system. In both cases, a variety of broadband mechanical excitations are used and the results analysed in the frequency domain. It is shown that although on/off control is more straightforward to implement, its performance is worse than the feedback linearisation strategy, and can be extremely sensitive to the excitation conditions

GA-tuning of nonlinear observers for sensorless control of automotive power steering IPMSMs

The paper considers two observer-based rotor position estimation schemes for sensorless control of interior permanent magnet synchronous motors (IPMSMs) for use in future automotive power steering systems. Specifically, emphasis is given to techniques based on feedback-linearisation followed by classical Luenberger observer design, and direct design of non-linear observers. Genetic algorithms (GAs), using the principles of evolution, natural selection and genetic mutation, are introduced to address difficulties in selecting correction gains for the observers, since no analytical tuning mechanisms yet exist. Experimental measurements from an automotive power steering test-facility are included, to demonstrate the enhanced performance attributes offered by tuning the proposed observer schemes, online, in this manner

Self-adaptive loop for external disturbance reduction in differential measurement set-up

We present a method developed to actively compensate common-mode magnetic disturbances on a multi-sensor device devoted to differential measurements. The system uses a field-programmable-gated-array card, and operates in conjunction with a high sensitivity magnetometer: compensating the common-mode of magnetic disturbances results in a relevant reduction of the difference-mode noise. The digital nature of the compensation system allows for using a numerical approach aimed at automatically adapting the feedback loop filter response. A common mode disturbance attenuation exceeding 50 dB is achieved, resulting in a final improvement of the differential noise floor by a factor of 10 over the whole spectral interval of interest.Comment: 7 pages, 8 figures, 26 ref

Design of robust service operations using cybernetic principles and simulation

Information flows in a service organisation allow business units to co-ordinate their response to changes in the operating environment. Processes and interactions can be designed so that the right information flows to the right people, at the right time to make effective decisions regarding job priorities and allocation of limited resource. This paper develops an analysis framework and simulation approach to identify the internal information flows an organisation needs to “tune itself” for changing conditions, thus making itself more robust to uncertainties. The ideas are developed and illustrated through a case study with a major telecoms company.International Design Conference - DESIGN 201

Process operating mode monitoring : switching online the right controller

This paper presents a structure which deals with process operating mode monitoring and allows the control law reconfiguration by switching online the right controller. After a short review of the advances in switching based control systems during the last decade, we introduce our approach based on the definition of operating modes of a plant. The control reconfiguration strategy is achieved by online selection of an adequate controller, in a case of active accommodation. The main contribution lies in settling up the design steps of the multicontroller structure and its accurate integration in the operating mode detection and accommodation loop. Simulation results show the effectiveness of the operating mode detection and accommodation (OMDA) structure for which the design steps propose a method to study the asymptotic stability, switching performances improvement, and the tuning of the multimodel based detector