A Data-driven Approach to Robust Control of Multivariable Systems by Convex Optimization

The frequency-domain data of a multivariable system in different operating points is used to design a robust controller with respect to the measurement noise and multimodel uncertainty. The controller is fully parametrized in terms of matrix polynomial functions and can be formulated as a centralized, decentralized or distributed controller. All standard performance specifications like $H_2$, $H_\infty$ and loop shaping are considered in a unified framework for continuous- and discrete-time systems. The control problem is formulated as a convex-concave optimization problem and then convexified by linearization of the concave part around an initial controller. The performance criterion converges monotonically to a local optimal solution in an iterative algorithm. The effectiveness of the method is compared with fixed-structure controllers using non-smooth optimization and with full-order optimal controllers via simulation examples. Finally, the experimental data of a gyroscope is used to design a data-driven controller that is successfully applied on the real system

Development of Glass Ionomer Cements with Improved Mechanical and Remineralizing Properties by Incorporation of 45S5 Bioglass®-Ceramic

Despite significant efforts to improve the clinical performance (e.g. mechanical and remineralizing properties) of glass ionomer cements (GICs), their essential characteristics such as proper translucency, adhesion to enamel and dentine, and fluoride-releasing capability cannot yet be fully exploited in load-bearing areas in restorative dentistry. The aim of this study is to introduce a functional approach to improve not only the mechanical properties of GICs, but also to enhance their biomineralizing capacity. In the first stage of this study, a series of versatile heat treatment profiles are used to tailor the crystallinity of 45S5 Bioglass® within a wide range of 5% to 100% via the formation of solely combeite as a mechanically competent yet bioactive phase. The resulting 45S5 glass-ceramics containing combeite not only are expected to retain beneficial levels of bioactivity, but also show improved mechanical properties compared to those of the amorphous 45S5 Bioglass®. By choosing the proper heat treatment from the proposed profiles in this study, different levels of mechanical properties and bioactivity in Bioglass® can be achieved according to the target application(s). In the second stage of this study, hybrid GICs with enhanced mechanical and remineralizing properties were developed via incorporation of an optimum amount (5 wt%) of 45S5 Bioglass®-ceramic particles with a certain degree of crystallinity. The effect of the degree of crystallinity of additives, which is completely overlooked in the current literature, was also addressed in this study. Mechanical properties testing, in vitro studies and microstructural analysis revealed that the Bioglass®-ceramic particles with 74% crystallinity best act as both remineralizing and reinforcing agents. Enhanced remineralizing and mechanical properties may not only broaden the hybrid GICs’ clinical applications but also can potentially enhance their in vivo performance. In the last stage of this study, a novel aluminum-free, 45S5 Bioglass®-based GIC with standard mechanical properties was produced. For the first time, 45S5 Bioglass® and its Bioglass®-ceramic were used as the GIC solid component. The Bioglass®-ceramic particles with 74% crystallinity was used as they favorably act as both remineralizing and reinforcing agents. The early stage progression of setting reaction was monitored. Bimodal particle size distribution was shown to improve the packing density and integrity of the set cement. In such GICs, not only the neurotoxicity of Al is eliminated, but chemical bond formation at cement/hard tissue(s) interface through interfacial biomineralization and adhesion is expected

Adjusted permutation method for multiple attribute decision making with meta-heuristic solution approaches

The permutation method of multiple attribute decision making has two significant deficiencies: high computational time and wrong priority output in some problem instances. In this paper, a novel permutation method called adjusted permutation method (APM) is proposed to compensate deficiencies of conventional permutation method. We propose Tabu search (TS) and particle swarm optimization (PSO) to find suitable solutions at a reasonable computational time for large problem instances. The proposed method is examined using some numerical examples to evaluate the performance of the proposed method. The preliminary results show that both approaches provide competent solutions in relatively reasonable amounts of time while TS performs better to solve APM

PID Controller Design for Multivariable Systems Using Gershgorin Bands

A method to design decentralized PID controllers for MIMO systems is presented in this paper. Each loop is designed separately, but the Gershgorin bands are considered to take interactions into account. The method uses different design parameters: The infinity norm of the complementary sensitivity function as well as the crossover frequency are considered to represent the closed-loop system performances. A third design parameter, defined as the minimal distance from the critical point to the Gershgorin band is used to provide the desired stability robustness to the MIMO closed-loop system