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Item type:Publication, Access status: without files , An interconnected systems approach to flow transition control(2014); This paper presents the application of an interconnected systems approach to the flow transition control problem. The control system consists of a network of local controllers with dedicated actuators and sensors. The measured feedback signals used by the controllers are the local changes in wall shear force, and the generated control action is a local change in fluid wall normal velocities. The approach presented here does not require periodicity of the channel as was required by most earlier approaches. Thus, in contrast to previously proposed control schemes which operate in Fourier domain, this approach works in physical domain. Secondly it does not restrict the number of interacting units, thus allowing the application of MEMS arrays. In order to synthesize such controllers, first the dynamics of the fluid is converted into interconnected system form. The model is validated using a non-linear simulation environment developed in FLUENT, and by analysing the growth in the transient energy. The model is then used to synthesize an interconnected controller. The simulated closed-loop response shows that the controller can delay the transition by reducing the transient energy.Publicationtype: Conference Paper68 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A hybrid approach to the synthesis of simply structured robust and gain-scheduled controllersFrequently in engineering applications, simply structured controllers are required for plants whose dynamics are either not fully known or varies with time. The problem of designing such structurally constrained controllers is known to be NP-hard. This paper presents a method for designing such controllers for both continuous-time and discrete-time uncertain or linear parameter varying (LPV) systems. The method relies on sufficient linear matrix inequalities (LMI) conditions also presented here. These LMIs are used to evaluate performance of a given controller in terms of the worst-case induced L2-norm for complete operational envelope. The strength of this LMI formulation lies in the fact that the robust performance evaluation condition is less conservative than standard results because it is based on a parameter-dependent Lypunov function and full block multipliers which allows to consider a bound on the rate of change in parameters. The LMI conditions are used in a hybrid evolutionary-LMI algorithm. The proposed algorithm employs evolutionary search to span the solution space and LMI solvers to find the worst case performance. The algorithm is independent of the controller structure, which allows to design simply structured controllers for complex systems in a systematic way. To illustrate the approach, two applications are presented: a distillation column and a spark ignition (SI) engine. For the distillation column, simple PI controllers with first order pre-filters are designed to achieve time and frequency domain control objectives in the presence of 20% input uncertainty. For the SI engine example, gain-scheduled PID controllers are designed and tuned. these examples illustrate that the proposed approach can be used to systematically design simply structured low-order controllers, while satisfying all performance requirements in terms of the worst-case induced L2-norm.Publicationtype: Journal Article16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Consistent identification of spatially interconnected systemsThis paper presents an identification technique to consistently identify multi-dimensional systems with additive output colored noise in transfer function representation. The method is an extension of a one-dimensional refined instrumental variable method to multi-dimensional systems. It can be used to identify models for multi-dimensional systems with Box-Jenkins structure; the method may give estimates with minimum bias and variance. In this paper we consider a general multi-dimensional system, which may be separable or non-separable, causal, semi-causal (spatially interconnected systems) or non-causal. Furthermore the algorithm can handle boundary conditions. The effectiveness of the method is shown with application to simulation examples. © 2011 AACC American Automatic Control Council.Publicationtype: Conference Paper27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Simply structured controllers for parameter varying distributed systemsThis paper presents a systematic approach to the synthesis of simply structured controllers for large scale parameter varying distributed systems. The design and optimization procedure consists of two loops. In an inner loop, an efficient LMI-based optimization algorithm is used to evaluate the closed-loop performance. The outer loop uses evolutionary operators to iteratively search for the parameters of a controller network that achieves the best performance. For the purpose of performance evaluation, new sufficient LMI conditions are presented to find the induced L2 norm of such systems. The conservatism of the analysis is reduced by the use of parameter dependent Lyapunov functions and by taking bounds on the parameter variation rates into account. Since the control algorithms are implemented on digital computers, the results are presented for discrete time and discrete space systems. The problem posed in this form is infinite dimensional, a gridding algorithm is also proposed to convert it into a finite dimensional problem. The approach is illustrated with two applications: active vibration control of a cantilever, and position control of a seismic cable. These examples illustrate that the performance analysis condition presented here is less conservative than previously presented LMI conditions. It is also demonstrated that the approach can be used to systematically design simply structured low-order controllers, while satisfying all performance requirements.Publicationtype: Journal Article10 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Transient energy analysis of a spatially interconnected model for 3D Poiseuille flowIn this paper a new model for 3D Poiseuille flow is presented. The model is based on applying a combined spectral-finite difference approach on the velocity-vorticity formulation of the Navier-Stokes equations. In 3D the dominating feature of the problem is non-normality of the eigenvectors. One measure to assess the non-normality is the transient energy response. The model is validated by comparing the maximum transient energy for two different cases; for both cases the Reynolds number is fixed at 5000, in the first case the span-wise spatial frequency is set to zero and the stream-wise spatial frequency is varied from 0.1 to 2, while for the second case the stream-wise frequency is set to zero and the span-wise frequency is varied from 0.1 to 3. It is known that for the first case the system is stable, while the second case is highly non-normal with maximum transient energy reaching 4500. It is observed that the model predicts both of these characteristics. Next, as a first step towards controller synthesis, a stabilizing state feedback controller is designed to minimize the transient energy response, by minimizing the induced L 2-norm. The closed loop response shows that the energy is reduced by the factor of 30. © 2010 AACC.Publicationtype: Conference Paper16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Consistent identification of two-dimensional systemsThis paper presents an identification technique to consistently identify two-dimensional (2-D) systems with additive output noise in transfer function representation. The method is an extension of a one-dimensional instrumental variable (IV) method to two-dimensional systems. In this paper we consider a general two-dimensional (2-D) systems, which may be separable or non-separable, causal, semi-causal (spatially interconnected systems) or non-causal. Furthermore the algorithm can handle boundary conditions. The effectiveness of the method is shown with application to simulation examples. © 2010 AACC.Publicationtype: Conference Paper13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Identification of LPV models for spatially varying interconnected systemsThis paper presents a method for system identification of two dimensional parameter varying systems. The idea of linear parameter varying (LPV) identification for one dimensional causal systems in input-output form is extended to identify two dimensional (2-D) parameter varying systems in input-output form which may be causal, semi-causal or noncausal. The identification method is general in the sense that it can be used to identify systems which may be separable or non-separable. Furthermore, the algorithm explicitly takes boundary conditions into consideration. The effectiveness of the approach is demonstrated by applying it to identify a spatially varying model for a non-uniform beam. © 2010 AACC.Publicationtype: Conference Paper16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Identification of spatially interconnected systems using neural networkThis paper presents an identification technique based on linear recurrent neural network to identify spatially interconnected systems both in open and closed-loop form. The latter has not been addressed in the literature for the systems under consideration. The paper considers identification of two-dimensional (time and space) systems; the method can be easily extended to have more than one dimension in space. In this paper we consider a semi-causal (causal in time and non-causal in space) two-dimensional (2-D) system, which may be separable or non-separable but the method can also be used for 2-D systems which are causal in both dimensions. Furthermore the algorithm can handle boundary conditions. The effectiveness of the method is shown with application to simulation examples.Publicationtype: Conference Paper11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Identification of spatially interconnected systemsThis paper presents a method for the identification of spatially interconnected system in rational form, using input-output data. Unlike previously proposed approaches, this method does not rely on a separability condition. The motivation for this approach is to identify a spatially interconnected model in Roesser form for which efficient control synthesis approaches have been recently proposed. The algorithm explicitly takes into consideration boundary conditions, which makes it suitable for boundary value problems such as conduction of heat through metal or vibration in fixed, simply supported or cantilever beams. The approach is illustrated by applying it to a beam element with various boundary conditions. The effectiveness of the method is demonstrated by a controller synthesis based on the identified model.Publicationtype: Conference Paper14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A hybrid gradient-LMI algorithm for the synthesis of LPV gain-scheduled controllersThis paper presents an algorithm for solving optimization problems with bilinear matrix inequality (BMI) constraints, which frequently appear in controller synthesis. The algorithm is based on a combination of gradient-based optimization and linear matrix inequalities (LMIs), which makes it fast and enables it to handle a large number of decision variables. Here it is used to synthesize fixed-structure and low-order gain-scheduled controllers for linear parameter varying (LPV) systems, using the idea of quadratic separation. It is known that the synthesis problem based on quadratic separation leads to BMIs. The synthesis technique is applied to design fixed-structure and low-order gain-scheduled controllers for a spark ignition engine, and results are compared with existing approaches to solve BMI constraint optimization problems. It turns out that the proposed algorithm gives solutions where other approaches may fail.Publicationtype: Conference Paper22