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The control algorithm is the core aspect to realize vibration mitigation effectively for the intelligent system. In this chapter, equations of the motion of an intelligent vibration control system are introduced firstly, and fundamental theories of different control algorithms for intelligent vibration control system are introduced in detail. At the same time, the advantages and disadvantages of each algorithm are summarized as well as its applicable condition.

In this chapter, design and parameters optimization on intelligent control devices are introduced. Magnetorheological (MR) damper and MR elastomer are designed optimally as examples of semi-active control devices. The active control devices are also designed based on the control force optimization.

The basic principle of semiactive intelligent control method is introduced firstly, and then the commonly used semiactive control devices, such as magnetorheological (MR) damper, electrorheological damper, piezoelectricity friction damper, semiactive-varied stiffness damper, semiactive-varied damping damper, and MR elastomer device, are introduced in detail including basic principles, construction and design, mathematical model, analysis and design methods, test and applications.

The analytical method of the structures incorporated with magnetorheological (MR) dampers, including the elastic analysis and elasto-plastic analysis, is introduced. In this chapter, taking the building structure with MR dampers as an example, the models of the structure and dampers will be discussed. Finally, the dynamic response analysis method based on SIMULINK is introduced.

The control algorithm and theoretical dynamic analysis method of the intelligent controlled structure have been presented in detail in the previous chapters; this chapter will focus on the specific numerical examples. The building structure with magnetorheological (MR) dampers, the bridge with MR dampers, and the platform with MR elastomer devices are chosen to evaluate the control effects of the semiactive intelligent control devices. The building structure with active tendon system is taken as an example to verify the control effect of active control.

The intelligent vibration control strategies are applied to real structures through the intelligent controller, thus the hardware design of the intelligent controller is very important to the effectiveness of intelligent control of civil engineering structures. In this chapter, the intelligent controller of magnetorheological dampers is taken for example to introduce the hardware design method of intelligent controllers, and then experimental study is carried out to verify the effectiveness of the intelligent controllers.

In this chapter, principles and classifications of active intelligent control systems are introduced firstly, and basic contents of the active mass control system and active tendon control system, including the basic principles, the mathematical model, structural analysis, and engineering examples are presented. Finally, other active intelligent control systems are introduced briefly.

Persulfate oxidation processes, with and without activation using ultraviolet light (respectively UV/PS and PS) have the potential to degrade anthropogenic chemicals in water. However, little is known about the impact of PS or UV/PS pre-oxidation on downstream formation of disinfection by-products (DBPs). In this study the three antibiotic chloramphenicols (chloramphenicol and two of its analogues [thiamphenicol and florfenicol], referred to collectively as CAPs), which frequently occur in wastewater-impacted source waters used by drinking water treatment plants, were selected as model antibiotic compounds. The formation of carbonaceous and nitrogenous disinfection by-products, including halomethanes, haloacetonitriles and halonitromethanes, during chlorination and chloramination preceded by PS and UV/PS was investigated. No significant concentrations of haloacetonitriles and halonitromethanes were detected during chlorination. During chloramination chloramphenicol formed a considerable amount of dichloronitromethane (e.g., 3.44 ± 0.33% mol/mol at NH2Cl dose = 1 mM) and trichloronitromethane (e.g., 0.79 ± 0.07% mol/mol at NH2Cl dose = 1 mM), compared with THM and HAN formation. PS pre-oxidation achieved a statistically significant reduction in trichloromethane formation from chlorination, and in HAN and HNM formation from chloramination. Although UV/PS slightly increased dichloroacetonitrile formation during chloramination, it significantly decreased dichloronitromethane and trichloronitromethane formation during chloramination. Overall, the use of PS and UV/PS has the potential to have contrasting impacts on DBP formation in heavily wastewater-impacted waters, depending on the disinfection method. Hence, their application needs to be carefully balanced against the downstream effect on DBP formation.