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This paper suggests another approach to eigenstructure assignment in a polynomial matrices framework. In particular, the design of eigenstructure assignment is performed without selecting initial eigenvalues. The eigenspaces of the system are handled in polynomial matrices format, where the closed-loop transfer function of the system is expressed as a coprime factorisation. The controller structure...
For linear systems with structured uncertainties, the unknown input fault detection observer (UIFDO) provides a robust diagnostic approach by decoupling the fault signals from the unknown input term. However, in real applications, detection performance of the UIFDO degrades seriously as nonlinearities become significant in a wide dynamic operating range. In this paper, a novel UIFDO design and the...
The discrete-time systems with constraints are probably the most important class of systems in practice due to the fast development of computer and its applicaiton in control area. For discrete-time linear systems with input amplitude and rate constraints, we characterize the generalized stability region and give algorithms to find the vertex and facet of this region
This paper deals with fault detection observer design for linear time-invariant systems with unknown inputs. The design objective is set to minimize a combined performance index Hinfin/H- which means to achieve a good compromise between robustness to the disturbance and sensitivity to the fault. Hence, the fault detection observer is designed to detect the fault of smallest energy possible. In this...
In this paper, we propose a design method of a disturbance-accommodating gain-scheduled control taking account of actuator saturation by seismic excitation in vibration isolation for a multi-degree-of-freedom structure. A disturbance model multiplied by an envelope function is introduced for disturbance-accommodating control in order to represent the nonstationary characteristics of seismic disturbance...
The paper presents a method for energy efficiency analysis of servo pneumatic actuator systems. Simulation study indicated that different quantities of compressed air were consumed for one cycle of piston movement when the same controller is adopted but with different profiles for servo pneumatic actuators. This motivated the authors to investigate the profile which leads the system to use the least...
Motivated by research into tumour tracking in radiotherapy, this paper considers the problem of constructing a linear time-invariant asymptotic estimator to predict the tumour location in real time. The challenge in the estimator design is to accommodate a time delay associated with the sensor, which in this case is an X-ray imager and associated image processor. The contributions of this paper are...
This paper deals with the parameter identification of a model for the dynamic behavior of a large industrial centrifugal compression system. Experimental results are presented to evaluate a new approach for determining the parameters of a modified version of the well-known Greitzer model. This approach is based on an approximate realization algorithm that constructs an LTI model from step response...
The design of a indirect self-tuning power system nodal voltage regulator is presented. A recursive least-squares (RLS) algorithm with variable forgetting factor estimates at each sampling period the parameters of a suitable discrete-time linear model that describes in an approximated way the system dynamics from the regulation node. The proposed model comprises both an unknown bias representing the...
This paper describes a controller design and also a sensor fault diagnosis based on a LTV model for a winding machine. It shows that, according to an experimental identification approach, a LTV model is ideally suited to improve the control of web tension. Moreover, based on this model, an innovative bank of interpolated LTI Kalman filters is synthesised to allow sensor fault detection and isolation...
In this paper, we deal with the issue of robust delay-independent asymptotic stability and robust disturbance attenuation problem for linear parameter-dependent systems. Using Hamiltonian-Jacoby-Isaac approach, a parameter-dependent LMI optimization is obtained. It is shown that by utilizing polynomial parameter-dependent quadratic Lyapunov functions, a parameter-dependent LMI optimization problem...
In this paper, switching control of linear time-invariant systems using generalized sampled-data hold functions is investigated. It is assumed that the plant model belongs to a finite set of known plants. The output of the system is periodically sampled and a control signal is being generated by means of a suitable hold function which solves the robust servomechanism problem for a family of plant...
Formation flying is an enabling technology for many future space missions. This paper presents an MPC (model predictive control) controller that uses dynamics based on a modified version of Gauss' variational equations which incorporates osculating J2 effects. A linear parameter-varying version of existing dynamics is developed, creating a highly accurate model that can easily be embedded in the MPC...
This paper presents optimal mean-square linear combinations of arbitrary number of local estimates. In particular, for two estimates, these combinations represent the Millman and Bar-Shalom-Campo formulas for uncorrelated and correlated estimates, respectively. These new results are applied to the linear filtering problem. The suboptimal two-stage filter for linear dynamic systems is designed: the...
First principle models and empirical models are necessarily approximate. In this paper we develop two empirical approaches that use a delta model to modify an initial model by means of cascade, parallel or feedback augmentation. A sub-space based nonlinear identification algorithm and an adaptive disturbance rejection algorithm are both used to construct the delta model. Three classes of errors in...
The paper presents the first application of lscr1 optimization theory to terminal guidance. The novel design approach accounts for a bounded disturbance representing the unknown evasive tactic of the target, a noise signal affecting the measurements, and a saturation limit on the actuators of the pursuer. The resulting lscr 1 guidance law is a linear output-feedback controller. The performance of...
This paper develops a representation of multi-model based controllers using graph theory and artificial intelligence techniques. These techniques are neural networks and genetic algorithms. Thus, graph theory is used to describe in a formal and concise way the switching mechanism between the various plant parameterizations of the switched system. Moreover, the interpretation of multimodel controllers...
This paper deals with robust stability and control of uncertain discrete-time linear systems with Markovian jumping parameters. Systems with polytopic-type parameter uncertainty in either the state-space model matrices, or in the transition probability matrix of the Markov process, are considered. This paper develops new methods of robust stability analysis and robust stabilization in the mean square...
This paper deals with the robust iterative learning control (ILC) design for uncertain single input-single output (SISO) linear time invariant (LTI) systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the mu-synthesis approach to obtain a feedback controller. Thereafter, a convergent iterative rule is obtained in a straightforward...
This paper proposes LMI conditions to estimate the robustness of uncertain matrices with respect to root-clustering regions (any intersection and/or union of half planes, discs and outsides of discs). The uncertainty complies with a polytopic LFT description. This robustness criterion enables, as a special case, to derive a non fragility index for a pole placement by output feedback gain. It is then...
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