Online Utility-based Supervisory Control of Water Recovery Subsystem in ALS systems Sherif Abdelwahed Wu Jian (presenter) Gautam Biswas Institute for Software Integrated Systems Vanderbilt University Introduction An online supervisory control scheme for efficient resource management in complex embedded systems, such as the Water Recovery System (WRS) of Advanced Life Support (ALS) Systems. System components and their interactions are modeled as a switching hybrid system automata. Performance specification is represented as a utility function. The maximization of system utilities problem is formulated as a safety control problem. A limited-horizon online supervisory controller is used to achieve the desired specification. The online controller explores a limited region of the state-space of the system at each time step and decides the best action accordingly. The feasibility and accuracy of the online algorithm can be assessed at design time. Model Development The Control Problem Given a switching hybrid system H with state space X and input set R The set point spec. is given as a region X s  X and a set of initial states X o  X The control problem is to derive the system from any state in X o to X s in finite time using finite sequence of inputs In addition the supervisor is required to maintain the system within X s Online Control Approach Selection of the next step is based on a map that defines how close the current state is to X s Controller constructs a tree of all future states up to certain depth. A path that minimizes the distance to X s is traced back to current state and the initial step is selected. Current state Set-point region Minimum distance state Next control input Optimal path KK+1K+N… Simulation Results The figures below (in black lines) show the system performance under the online supervisory control. The figures (in blue dotted lines) show the behavior of the system under online control in the presence of fault. A block in a pipe was introduced at time t = 400 and was isolated at time t = 430. The online controller managed to compensate for the fault by increasing the time spent in the primary. The overall average utility in this case was only 0.93% less than the utility in the nominal situation. Control Structure System performance is captured using a utility function that defines the relative importance of water outflow vs. water quality. The controller is required to maximize the following utility Here K(i) is the water quality and f 3 (i) is the water outflow at time i, S v is the penalty for switching and N is the depth of the exploration tree. WRS MatLab Simulink Model Mathematical Model Real data Simulated data Utility Module RO System Model RO System Input Selection Tree(x(k)) u(k) x(k) x(i) next input Discussion: Performance Evaluation The figures shows the changes in utility and number of explored states/step w.r.t. the exploration depth. Increasing the depth significantly affect the average computational complexity without major change to the overall utility. Acknowledgement This work was supported in part through the NASA-ALS grant NCC and NSF ITR grant CCR Example: Control of Reverse Osmosis Subsystems of WRS, and simulation results can be found at bottom right