158
Chapter Seven
Conclusion and Recommendations for Future Work
159
have neglected the fact that a HVAC plant consists of various components, which have to work together simultaneously and are required to operate under continuous changing dynamics and environmental conditions.
Moreover, the control approach followed in most HVAC system designs was single-variable controllers, such as the proportional-integral-derivative (PID) controller, which measures one controlled variable and applies a corrective control effort in a repetitive manner. The PID controller can be a good solution when it is confined to one specific condition, however, with the variations in the operating condition, which is the nature of HVAC system operation, it has to be tuned repeatedly and it becomes an exhausting process consuming extra efforts.
Consequently, this study has adopted a HVAC system model considering air conditioning function that consists of all the major components, including the chilled water pump, inlet and outlet fans, ventilated volume and ducts networking that work simultaneously as an integral whole so that the resulted mathematical model is a 3 inputs-3 outputs multivariable system model. Another modelling consideration that has been included in the study is the spatial nature of the slender long ventilated volume as a dimensionally dispersed system where the physical properties of the object are distributed and not lumped mass elements. Meanwhile, the fan motors, inlet and exit impedances are of physical properties that can be treated as concentrated lumped mass elements without compromising on the accuracy. The final obtained model based on the aforementioned modelling improvements has been adopted from the HVAC hybrid distributed-lumped parameter model developed by Whalley R. and Abdul-Ameer A. (2011) as a readily derived HVAC system model due to its robustness and accuracy. The four research objectives set in chapter 1, were found to be fulfilled and can be reviewed and explained as follows:
160
i. Different nine-time domain responses of the hybrid distributed-lumped parameter HVAC systems mathematical model developed by Whalley R. and Abdul-Ameer A. (2011) have been examined, so that the actual dynamical characteristics of the system were identified and acknowledged. This process was achieved by identifying x-y coordinates of each time domain system response and feeding such coordinates into MATLAB software, so that MATLAB was introduced to the dynamical characteristics of the HVAC open loop system model.
ii. Nnecessary frequency domain transfer functions employing MATLAB Tool-Box to handle and process HVAC system time domain mathematical model responses developed in (i) so that (3 3 ) transfer function matrix was obtained. Simulating the frequency domain responses gave an approximately 98% fit with the time domain responses so that similar dynamical characteristics were also maintained and acknowledged by the frequency domain representations. The input-output relationship in Laplace (s) variable representation is shown in Equation 4.2 and the open loop system responses are shown in Figure 4.7, 4.8 and 4.9.
iii. Based on the HVAC open loop transfer function matrix in the frequency domain, designing a controller and enabling system analysis can be a straightforward process. The HVAC system control strategy based on the LE control procedures outlined by Whalley R. and Ebrahimi M. (2004) has and applied so that minimized control system energy dissipation, adequate disturbance suppression, superior system performance in terms of integrity, and closed loop stability have been achieved. The LE controller was the main control technique employed in this study. It employs output feedback, passive compensators and proportional
161
gains for multivariable process industries. The controller design employs two major control loops. The desired dynamics and transient responses are designed by the inner control loop while the outer loop is configured to improve the system steady state error and disturbance rejection. Good results and well-behaved system performance have been obtained by the LE controller. LE control technique managed to minimize the control system energy dissipation associated with good system performance in terms of integrity and closed loop stability. It has also shown acceptable performance in terms of reducing the coupling between the output signals and adequate disturbance suppression.
iv. To enable theoretical validation for the performance of the LE controller, a detailed comparison between the LE controller and alternative multi-variable control technique, namely Direct Nyquist Array (DNA) has been explored. The DNA procedure is based on reducing the interactions between system outputs by decoupling them through a decoupling matrix, so that a closed loop control technique can be applied on each loop independently.
Contrasting the straightforward procedure used to decouple the interaction between the outputs in the LE controller, the decoupling matrix in the DNA controller was based on a trial and error approach, which was very time consuming. The order of the computed compensators of the decoupling matrix in the DNA control technique were of 9th and 11th orders that can be very complicated. Although the system under the DNA controller was able to regulate and control the HVAC multivariable system, having high proportional control energy cost makes the solution to contravene with global efforts to minimize energy consumption inside buildings. Moreover, the system responses in the DNA control technique were slower than same responses in the LE controller. With the exception of the LE behaviour in supressing the disturbance exerted in the pressure output which was not
162
completely well, the LE control is superior to the DNA control solution when considering the simplicity of each controller, the system behaviour under closed loop control and the control energy dissipated by each controller which is the key judgment.
Minimised control dissipation achieved by the LE controller makes it the ideal solution for HVAC system regulation, especially given the global attention encouraging sustainable technology and least energy consumption. Moreover, using simple gains and pre-compensators calculated based on values that make the Performance Index minimum and based on avoiding employment of the integrators, were the main reasons for achieving minimized control energy dissipation. This would be reflected in lower energy bill values and the operational cost for such a HVAC system under the LE controller, achieving least actuator activity, least heat and wear and achieving maintenance cost minimization.