86 research outputs found
Porosity and Micro-Hardness of Shrouded Plasma Sprayed Titanium Coatings
Titanium and its alloys are often used as key materials for corrosion protection. A promising approach to optimize both mechanical properties and corrosion resistance is the use of
coating technologies. In this paper, shrouded plasma spray was used as a useful technology to produce low oxide containing titanium coatings. A solid shroud was used to plasma spray titanium coatings to reduce the oxide content. The titanium coatings were assessed by optical microscope, scanning electron microscopy and Vickers microhardness testing. The results showed that the shrouded titanium coatings exhibited an enhanced microstructure. The presence of the shroud and
shroud gas flow led to a significant reduction in coating porosity because the reduction in air entrainment with the shroud resulted in better heating of the particles. The shrouded titanium coatings had a lower value of Vickers microhardness and a relative lower standard deviation than the air plasma sprayed titanium coatings
On output tracking using dynamic output feedback discrete-time sliding-mode controllers
This is the author's version of an artiucle subseqiently published in IEEE Transactions on Automatic Control. The definitive published version is available via doi: 10.1109/TAC.2007.904256In this note, an output feedback based discrete-time sliding-mode control scheme is proposed. It incorporates a steady-state tracking requirement through the use of integral action. Previous work has shown that with an appropriate choice of sliding surface, discrete-time sliding-mode control can be applied to nonminimum phase systems. The original scheme employed static output feedback and this imposed restrictions on the class of systems to which it was applicable - specifically a certain "fictitious" subsystem was required to be output feedback stabilizable. The scheme proposed in this note includes a compensator which broadens the class of systems for which the results are applicable. In the presence of bounded matched disturbances, ultimate boundedness results are obtained. It is also shown that in the presence of a class of sector bounded uncertainty, asymptotic stability can be achieved. © 2007 IEEE
Arbitrary Pole Placement with Sliding Mode Control
This paper considers the problem of placing all the poles arbitrarily for a linear time-invariant plant with the linear part 00 sliding mode control. We solve this problem in two ways. In the first approach, we design a sliding mode control by specifying the desired pole locations. The closed-loop system under this control law has all eigenvalues at the desired places. In the second approach, the sliding mode control is designed from a given state feedback gain so that all the poles of the closed-loop system are placed at the same location as that of the state feedback controller. Here, we provide a necessary and sufficient condition for the existence of a linear gain using the sliding mode control to achieve the desired pole assignment. This condition is always fulfilled for the single input case whereas it is only applicable for certain multi-input scenarios that meet the conditions stated in the paper. In both the approaches, one can place the closed-loop poles with the proposed sliding mode control at any arbitrary location in the left half of the complex plane, unlike with traditional design, where m poles are at the origin with m being the number of control inputs. A numerical example illustrates the proposed design methodology for sliding mode control
Output feedback robust distributed model predictive control for parallel systems in process networks with competitive characteristics
The parallel structure is one of the basic system architectures found in process networks. This paper formulates control strategies for such parallel systems when the states are unmeasured. The competitive coupling and competitive constraints are addressed in the control design. A distributed buffer and pre-estimator are proposed to solve problems relating to coupling and timely communication whilst a distributed moving horizon estimator is employed to further improve the estimation accuracy in the presence of the constraints. An output feedback robust distributed model predictive control algorithm is then developed for such parallel systems. The Lyapunov method is used for the theoretical analysis which produces tractable linear matrix inequalities (LMI). Simulations and experimental results are provided to validate the effectiveness of the proposed approach
Static Output Feedback Model Predictive Control for Uncertain Linear Systems
A static output feedback model predictive control algorithm is proposed for an uncertain linear continuous system. An explicit expression for the static output feedback control law is developed in light of the projection lemma. An infinite time domain optimization problem is transformed into a linear programming problem. The solvability of the optimization problem and the stability are proved to underpin the proposed approach. The effectiveness of the proposed method is validated by using case studies
On the solvability of the constrained Lyapunov problem
Journal ArticleThis paper considers system theoretic conditions for the solvability of the so-called constrained Lyapunov problem for nonsquare systems. These problems commonly appear in the control systems literature. Both a static output feedback problem and an observer problem are considered. The basis for the work described in this paper is a new canonical form that simplifies the analysis and deals with the equality constraint in a simple way. © 2007 IEEE
Disturbance observer based sliding mode control for a continuous stirred tank reactor (CSTR)
A continuous stirred tank reactor (CSTR) is typical of equipment found in the process control industry. The dynamics represent a wide class of second order nonlinear systems and thus as well as having specific industrial application, control of the CSTR is frequently used as a benchmark problem for application and testing of new control algorithms. Due to the high complexity of the CSTR system, the robust control design problem is challenging. This paper first establishes a mathematical model of the system. A disturbance observer is then designed to estimate the disturbance and a corresponding asymptotically stable sliding mode control is developed. Stability analysis is presented in terms of the Lyapunov method. Finally, based on experimental data, the proposed method is validated using simulation experiments
A Robust Exact Differentiator Toolbox for Matlab®/Simulink®
This paper demonstrates the functionality and ease of use of a recently implemented robust exact differentiator block for numerical simulations performed within the Matlab/Simulink software environment. It is demonstrated that the differentiator block may be used for various applications and may be easily integrated within existing Simulink models. The underpinning discrete-time differentiation algorithm is briefly outlined and its parameters for differentiator orders up to 10 are presented. An extended version of the toolbox supports the so-called automatic code generation feature of Matlab/Simulink. This functionality allows compilable code to be produced for many available hardware platforms. Three applications are presented in the paper, two of which require the generation of executable code. The third simulation-based application presents a differentiator based edge detection algorithm for image processing purposes which directly utilises the Simulink block. The three applications employ differentiators of order 4, 3 and 2, respectively
Robust Sliding Mode Observers for Large Scale Systems with Applications to a Multimachine Power System
Distributed model predictive control for the atmospheric and vacuum distillation towers in a petroleum refining process
This paper develops a distributed model predictive control strategy for the atmospheric and vacuum distillation tower, which constitutes a key process involved in refining petroleum. When considering an MPC implementation, it is known that computational complexity can be reduced if the system is first decomposed into multiple smaller dimensional subsystems. Optimally exploiting the modern computer networks available in industry, a distributed model predictive control implementation is developed for the atmospheric and vacuum tower system, which is assumed to be part of a wider petroleum refining process comprised of a number of sub-systems connected in series. For each subsystem, given the availability of mutual communication channels between subsystems and by using an iterative calculation approach, it will be seen that Nash optimality can be achieved. A low-cost solution that is readily implementable online is seen to achieve the control objective. The effectiveness of the approach presented in the paper is validated by the results of nonlinear simulation experiments
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