- Electrical and Electronic Engineering - Research Publications
Electrical and Electronic Engineering - Research Publications
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ItemA UNIFYING FRAMEWORK FOR ANALYSIS AND DESIGN OF EXTREMUM SEEKING CONTROLLERSNesic, D ; Tan, Y ; Manzie, C ; Mohammadi, A ; Moase, W (IEEE, 2012-01-01)We summarize a unifying design approach to continuous-time extremum seeking that was recently reported by the authors. This approach is based on a feedback control paradigm that was to the best of our knowledge explicitly summarized for the first time in this form in our recent work. This paradigm covers some existing extremum seeking schemes, provides a direct link to off-line optimization and can be used as a unifying framework for design of novel extremum seeking schemes. Moreover, we show that other extremum seeking problem formulations can be interpreted using this unifying viewpoint. We believe that this unifying view will be invaluable to systematically design and analyze extremum seeking controllers in various settings.
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ItemTrajectory-based proofs for sampled-data extremum seeking controlKHONG, S ; Nesic, D ; Tan, Y ; Manzie, CG (IEEE, 2013)Extremum seeking of nonlinear systems based on a sampled-data control law is revisited. It is established that under some generic assumptions, semi-global practical asymptotically stable convergence to an extremum can be achieved. To this end, trajectory-based arguments are employed, by contrast with Lyapunov-function-type approaches in the existing literature. The proof is simpler and more straightforward; it is based on assumptions that are in general easier to verify. The proposed extremum seeking framework may encompass more general optimisation algorithms, such as those which do not admit a state-update realisation and/or Lyapunov functions. Multi-unit extremum seeking is also investigated within the context of accelerating the speed of convergence.
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ItemOn a Shubert Algorithm-Based Global Extremum Seeking SchemeNesic, D ; Nguyen, T ; Tan, Y ; Manzie, C (IEEE, 2012)This paper adapts the so-called Shubert algorithm for Extremum Seeking Control (ESC) to seek the global extremum (in presence of local extrema) of general dynamic plants. Different from derivative based methods that are widely used in ESC, the Shubert algorithm is a good representative of sampling optimization methods. With knowledge of the Lipschitz constant of an unknown static mapping, this deterministic algorithm seeks the global extremum. By introducing “waiting time” the proposed Shubert algorithm-based global extremum seeking guarantees the semi-global practical convergence (in the initial states) to the global extremum if compact sets of inputs are considered. Several numerical examples demonstrate how proposed method may be successfully deployed.
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ItemOn sampled-data extremum seeking control via stochastic approximation methodsKhong, SZ ; Tan, Y ; Nesic, D ; Manzie, C (IEEE, 2013-01-01)This note establishes a link between stochastic approximation and extremum seeking of dynamical nonlinear systems. In particular, it is shown that by applying classes of stochastic approximation methods to dynamical systems via periodic sampled-data control, convergence analysis can be performed using standard tools in stochastic approximation. A tuning parameter within this framework is the period of the synchronised sampler and hold device, which is also the waiting time during which the system dynamics settle to within a controllable neighbourhood of the steady-state input-output behaviour. Semiglobal convergence with probability one is demonstrated for three basic classes of stochastic approximation methods: finite-difference, random directions, and simultaneous perturbation. The tradeoff between the speed of convergence and accuracy is also discussed within the context of asymptotic normality of the outputs of these optimisation algorithms.
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ItemExtremum Seeking Methods for Online Automotive CalibrationManzie, C ; Moase, W ; Shekhar, R ; Mohammadi, A ; Nesic, D ; Tan, Y ; Waschl, H ; Kolmanovsky, I ; Steinbuch, M ; del Re, L (Springer, 2014-01-01)The automotive calibration process is becoming increasingly difficult as the degrees of freedom in modern engines rises with the number of actuators. This is coupled with the desire to utilise alternative fuels to gasoline and diesel for the promise of lower CO2 levels in transportation. However, the range of fuel blends also leads to variability in the combustion properties, requiring additional sensing and calibration effort for the engine control unit (ECU). Shifting some of the calibration effort online whereby the engine controller adjusts its operation to account for the current operating conditions may be an effective alternative if the performance of the controller can be guaranteed within some performance characteristics. This tutorial chapter summarises recent developments in extremum seeking control, and investigates the potential of these methods to address some of the complexity in developing fuel-flexible controllers for automotive powertrains.
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ItemMulti-agent gradient climbing via extremum seeking controlKong, SZ ; Manzie, CG ; Tan, Y ; Nesic, D (IFAC - International Federation of Automatic Control, 2014)A unified framework based on discrete-time gradient-based extremum seeking control is proposed to localise an extremum of an unknown scalar field distribution using a group of equipped with sensors. The controller utilises estimates of gradients of the field from local dithering sensor measurements collected by the mobile agents. It is assumed that distributed coordination which ensures uniform asymptotic stability with respect to a prescribed formation of the agents is employed. The framework is useful in that a broad range of nonlinear programming algorithms can be combined with a wide class of cooperative control laws to perform extreme source seeking. Semi-global practical asymptotically stable convergence to local extrema is established in the presence of bounded field sampling noise.
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ItemMultidimensional global extremum seeking via the DIRECT methodKhong, SZ ; Manzie, C ; Nesic, D ; Tan, Y (IEEE, 2012-01-01)This paper adapts the DIRECT method with a modified termination criterion for global extremum seeking control of multivariable dynamical plants - DIRECT is a sampling type global optimisation method for Lipschitz-continuous functions defined over compact multidimensional domains. Finite-time semi-global practical convergence is established based on a deadbeat sampled-data control law, whose sampling period is a parameter which determines the region and accuracy of convergence. A crucial part of the development is dedicated to a robustness analysis of the DIRECT method against bounded additive perturbations on the objective function. A numerical example of global extremum seeking in the presence of local extrema based on DIRECT is presented at the end.
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ItemExtremum seeking methods for online optimization of spark advance in alternative fueled enginesMohammadi, A ; Manzie, C ; Nešić, D (Elsevier, 2012-01-01)Alternative fueled engines offer greater challenges for engine control courtesy of uncertain fuel composition. This make optimal tuning of input parameters like spark advance extremely difficult in most existing ECU architectures. This paper proposes the use of greybox extremum seeking techniques to provide real-time optimization of the spark advance in alternative fueled engines. The ability and flexibility of the proposed framework is demonstrated through simulation examples. The approaches demonstrated may be extended to other engine inputs requiring online optimization.
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ItemOnline optimization of spark advance in alternative fueled engines using extremum seeking controlMohammadi, A ; Manzie, C ; Nesic, D (Elsevier, 2014-08-01)Alternative fueled engines offer greater challenges for engine control courtesy of uncertain fuel composition. This makes optimal tuning of input parameters like spark advance extremely difficult in most existing ECU architectures. This paper proposes the use of grey-box extremum seeking techniques to provide real-time optimization of the spark advance in alternative fueled engines. Since practical implementation of grey-box extremum seeking methods is typically done using digital technology, this paper takes advantage of emulation design methods to port the existing continuous-time grey-box extremum seeking methods to discrete-time frameworks. The ability and flexibility of the proposed discrete-time framework is demonstrated through simulations and in practical situation using a natural gas fueled engine.
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ItemEmulation Design for a Class of Extremum Seeking Controllers: Case Studies in ABS Design and Spark Timing CalibrationMohammadi, A ; Nesic, D ; Manzie, C (IEEE, 2013-01-01)The vast majority of extremum seeking designs in the literature are in continuous-time, however their practical implementation is typically done using digital technology. In this paper, a sampled-data implementation of extremum seeking controllers using emulation design methods is studied to address this gap. The conditions under which the emulated controller preserves the performance of the continuous-time plant are investigated. The main result also provides a guideline on how to tune the controller parameters including sample period in order to achieve the desired performance. The examples of anti-lock braking and spark timing calibration are used to illustrate the proposed design method through simulation and experimental tests.