The above mentioned control system was installed and tested in an experimental test cell with a south facing glazed surface. The changeable geometry of the transparent part of the test cell was achieved with an externally fixed motorized PVC roller blind controlled by a programmable logic controller (PLC) connected to a PC and an operator panel. The algorithms for the fuzzy thermal and illumination controllers were developed in the IDR BLOCK environment and were loaded in the PLC [3, 4]. For supervision, visualization and setting up of experiments a remote personal computer was used, although the communication with the PLC could also be achieved by using the operation panel. All of the obtained values and process variables were collected and stored in the PC, with an application developed especially for this purpose in Factory Link environment. The basic framework and functioning of the system is presented in Fig. 1.

The controller can be in general split into two control loops. These can function separately or, if desired, can be linked to work simultaneously. The first loop is the “illumination loop” comprising of elements or blocks, which make the roller blind alternations possible in such a way that the indoor set­point illumination is followed as closely as possible. The second is the “thermal loop” which is split in two separate controllers, one for the summer season (cooling mode) and the other for the winter season (heating mode). In the thermal loop there are also separate controllers for the functioning of electric heaters and a ventilator intended for passive cooling. Both control loops are designed as a cascade control system where fuzzy controller is used as the main controller and PID/V type controller as the auxiliary one [4]. In this way the main fuzzy controller defines roller blind position according to the external conditions and the set-point values. The PID/V controller then executes the appropriate change and position of the external roller blind.

1.1 Control loops

The thermal control loop used in the regulation system of the test chamber is the result of modelling and simulation approach. It derives from the thermal theoretical mathematical model [5, 6] executed in the MATLAB/SIMULINK environment. After numerical simulations conducted within the SIMULINK environment the controller fuzzy rules were fine-tuned through experimental work on the test chamber. The thermal loop is split into two separate fuzzy controllers dedicated to guide the position of the roller blind during summer (cooling) and winter (heating). During spring and autumn both controllers are used and act simultaneously in the determination of the position of the roller blind. The controllers are structured to closely follow the internal set point temperature parameters in correlation to the outside weather conditions. Each fuzzy controller contributes its part to the final decision on the positioning of the blind. The contributed part of the controller is determined on the basis of the difference between the internal and external air temperatures and the amount of exerted influence is derived by the evaluation function. The evaluation function is presented below:

Output_signl = (fuzzy_roll_summer/100* T_error* 0.5) + (fuzzy_roll_winter/100* (100- T_error* 0.5) — fuzzy_roll_summer (winter) is the output signal of the appropriate fuzzy controller, T_error is the temperature difference between the external measured and the internal set-point value of air temperature [7].

When the external air temperature is lower than the internal set-point temperature, only the winter controller directs the roller blind, while in the reversed case (external air temperature being higher than

the internal) both fuzzy controllers contribute to the positioning of the roller blind. Thermal control loop also regulates the actions of additional actuators (heater and ventilator) installed in the test chamber. If these are enabled, they can be used to help regulate internal temperature. Nonetheless, the position of the roller blind is always the priority action as the system strives to use more energy efficient ways of regulation.

When the internal environment of the test cell is regulated solely with the thermal loop, the illuminance control loop has no effect on the regulation process. On the other hand, if both loops were used in harmonized mode, the priority in guiding the roller blind was always given to the illuminance loop, because people are more susceptible to changes in illuminance than in temperature levels. Also the expected illumination oscillations were in the range of 1000-5000 lx and the dynamics of changes is far grater than in temperatures. All of the above reasons make illuminance a much harder quantity to regulate than temperature. When the desired levels of internal illumination are achieved, the thermal loop takes over and directs the roller blind to follow the thermal set-point profile as closely as possible within the admissible illumination set point tolerance. Because the internal ilumination is a very complex process, the control loop parameters and fuzzy rules were not developed in the same way as in the case of the thermal loop. Instead of mathematical model and numerical simulations an experimental approach with the application of expert knowledge and trial and error process was used.

2. Experiments

The tests designed to investigate the potential benefits of automated shading on the cooling load reduction in the spring and autumn time were carried out in several sets to cover a wide range of different weather conditions. Weather during mid-seasons is prone to rapid daily fluctuations in temperatures as well as in the levels of solar radiation. Because of this the key part in setting up the controller was the appropriate tuning between the summer and winter components of the thermal control loop.

The two experiments presented in this paper were conducted with the thermal loop governing the actions of the roller blind. This means that illuminance fuzzy loop was switched off at all times and thus had no effect on the results of the experiments. The input fuzzy variables to the thermal controller were global solar radiation and the temperature difference between the set-point temperature and the measured indoor temperature. The output of the controller was movements of the roller blind and switching the ventilator and the heater on or off. Simultaneous functioning of the heater and the regulator was not allowed at any time. In the diagrams a completely exposed window is equivalent to 100 %, which correlates to a completely retracted roller blind. On the other hand, a fully shaded window is represented by 0 % (e. g. fully extended roller blind). Similar in the case of the heater and the ventilator their functioning is represented in the fraction of operational output (e. g. 0 %=off, 100 %=full output).