# Presentation: 682437

## Issues in Integrated Health Management of Life Support Systems

- Gautam Biswas and Eric-Jan Manders
- Vanderbilt University
- _[gautam.biswas@vanderbilt.edu](mailto:gautam.biswas@vanderbilt.edu)_***; ***_[http://](http://www.vuse.vanderbilt.edu/~biswas)__[www.vuse.vanderbilt.edu/~biswas](http://www.vuse.vanderbilt.edu/~biswas)_
- David Kortenkamp
- NASA Johnson Space Center/Metrica Inc
*Acknowledge: *S. Abdelwahed, G. Karsai, J. Wu, I. Roychoudhury, N. Mahadevan, P. Bonsasso, and S. Bell
- .

**Supported by NASA-ALS NCC 9-159 (Program Manager: Darrell Jan)**
**Acknowledge help from Lockheed (Lin, Hanford, Anderson), and JSC (Anderson, Ewert)**

## What is ISHM?

- Ability to maintain system safety, health, and performance over the life of the system
- Involves monitoring, control, fault diagnosis, adaptation, reconfiguration and maintenance
- Operates along a continuum of time scales
- Behaviors (_immediate_): monitoring and control
- Performance level (_short-term_): fault diagnosis, adaptation
- Health (_long-term_): mission performance, maintenance, reconfiguration

- Issue: What about humans in the loop?

## ISHEM Architecture

**Process**

**Behavior**
**Monitors**
**&**
**Diagnoser**

**Fault-adaptive**
**Controller**

**Control Loop**

**Resource**
**monitors**

**Planner**
**&**
**Scheduler**

**Human(s)**

**Decision Making Loop**

**Supervisory**
**Controller**

- Feedback
- Control

**ISHM**

**Short-term**
**issues**
- (keep system
- safe & operational)

**Long-term**
**issues**
- (focus on mission goals & needs)

**Prognosis**
**system**

**ISHEM Architecture**

## Life support systems

- Life support systems produce consumables for human crew members.  Consumables include oxygen, water, and food
- Life support systems process waste products such as carbon dioxide, waste water and solid waste
- Goal:  Closed-loop system in terms of material consumption
- Life support systems must be carefully controlled to create a habitable environment
- Faults in life support systems can threaten both the crew and the mission

## ISHEM issues for Life Support

- Life support systems pose several unique and significant issues including:
*Interacting subsystems*: Life support systems contain many different subsystems that all need to work together
*Multiple Time Scales*: The subsystems operate at very different time-scales
*Sensing*: The biological components of life support systems make sensing difficult.
*Decision-making*: Life support subsystems operate at different time-scales and require decisions both in fast, real-time situations and in slow, long-duration situations
*Human involvement*: Humans are a significant part of the life support system in that they produce and consume resources

## Surface Habitat -- Architecture

- Coupled systems
-   Crew chamber
-   Biomass
-   Air
-   Water
-   Thermal
-   Power Generation
-   Food
-   Waste
- Operate at widely differering time constants

## Interacting systems

**Implemented as a**
**discrete-time, **
**discrete-event **
**simulator**
**Biosim**

## ISHEM Architecture

**Process**

**Behavior**
**Monitors**
**&**
**Diagnoser**

**Fault-adaptive**
**Controller**

**Control Loop**

**Resource**
**monitors**

**Planner**
**&**
**Scheduler**

**Human(s)**

**Decision Making Loop**

**Supervisory**
**Controller**

- Feedback
- Control

**ISHM**

**Short-term**
**issues**
- (keep system
- safe & operational)

**Long-term**
**issues**
- (focus on mission goals & needs)

**Prognosis**
**system**

**ISHEM Architecture**

**Focus: Short-Term Issues**

## Fault adaptive controllers Self-Managing Systems

**Definition**
- Systems that can manage their resources efficiently to achieve their objectives in a dynamic environment and under varying operation requirements
**Advantages**
- Rapid adaptation to dynamic operating conditions
- Autonomy
- Automatic recovery from certain class of failures
**Application Domain**
- Space exploration systems
- Manufacturing, Avionics and Automation systems

## Fault-Adaptive Control Architecture

**Fault-Adaptive Control Architecture**

**Process**

**Hybrid**
**Observer**

**Fault**
**Detector**

**Hybrid Bond Graph**
**(HBG) Models**

**Models**

**State**
**Space**

**Temporal**
**Causal**
**Graph**

**Discrete**
**Time**

**Modes**

**Active State Model**

**Behavior Monitors**
**+ Diagnoser**

**Fault-Adaptive Controllers**
**+ Supervisor**

## Modeling Approach

- Integrated Modeling Paradigm
- Graphical Component-oriented Modeling (GME)  Physics-based models  Models tailored for specific applications
- Physics-based models: Hybrid Bond Graphs (nonlinearities, switching junctions); Block Diagrams
- Simulink/Stateflow Models – Energy and mass balance; crew schedule
- Discrete-time models – Online supervisory control
- Modeled: WRS, ARS, Habitat, Crew Activity, Power Generation, EVA Activity

## Water Recovery System

- Three subsystems
-  Biological Waste Processor (BWP)
-  dirty  water circulates in loop through packed bed + nitrifier tubes
-  cleaner organic contaminant-free water collects in GLS
-  control – two pumps + nitrifier cleaning
-  Reverse Osmosis (RO)
-  Membrane-based particulate inorganic waste removal
-   water circulates in loop – four modes of operation: primary, secondary, purge, and clean
-  clean water to PPS (not modeled), purged water to AES
-   Air Evaporation System (AES)
-   evaporates water from wick, heat exchanger cools down to retrieve pure water

- Two storage units:
-  (1) Waste Water Tank: capacity = 25 liters
-  (2)  Potable Water Tank: capacity = 650 liters
- Processing rate:  25 – 50 liters per day
- Power Consumption (nominal): BWP = 0.7kW, RO = 0.8 kW; AES = 1.2 kW

- Control: Two levels
- Local controllers for BWP,
- 	RO, and AES
- System Controller: WRS

## Air Revitalization System

- Details: CDRA in tight loop with crew chamber: removes CO2; O2 added to restore air quality
- Air flow: between 5 and 10 kg./hour; Cabin air = 25oC
- CRS: CO2 + H2 in:  CH4 (vented) + H20 produced (back to dirty water tank); Temp = 425oC
- processes 0.16 to 0.23 kg of C per hour when on (operates only during the day)
**Buffers:  (1) CO****2****: 4 kg (2) H****2****: 0.8 kg (3) O****2****:  10 kg  (N****2 ****storage not dealt with explicitly)**
**Power consumed: CDRA: 0.8 kW; CRS: 0.55 kW; OGS: 0.67 kW.**

- Three subsystems:
- CDRA – CO2 removal
- CRS – CO2 reduction,
- OGS  -- electrolysis of water
- 	into H2 and O2

## Hierarchical Control

**Controller**

**AES**
**System**

**Controller**

**Utility-based**
**Optimize**
**performance**

**Constraint-based**
**Distribution of resources**
**Weekly crew schedule**

**WRS **
**System**

**WRS**
**Controller**

**ARS**
**System**

**AES**
**Controller**

**Supervisory Controller**

**Power **
**Generation**

**Crew**
**Chamber**

**SABATIER**

**CDRA**

**RO**

**AES**

**OGA**

**LC-BWP**

**LC-RO**

**LC-AES**

**LC-CDRA**

**LC-SAB**

**LC-OGA**

**WRS **
**System**

**BWP**

**Crew**
**Scheduler**

## Use behavioral model to estimate future system states over the prediction horizon 

***t***

**0**

**Time**

**Start state**

**Current state**

- Obtain the sequence of control inputs that optimize desired utility function

- Apply the first control input in the sequence at time *t*; discard the rest

- Utility-based Limited Look Ahead Control

- Repeat the process at each time step

## Online Control Design

- Discrete time model of plant + transitions
- To choose best action, perform look ahead search up to *L* steps
- Define utility function
- Repeat for next time step – accommodates for faults and disturbances in system

## SIMA Challenge Problem

- 90 day surface Habitat Lander of Lunar South Pole
- 	(14 day + 14 night cycle)
- One time use of surface habitat
- Crew of four
- Our focus: Air, Water, Thermal, Crew Chamber, Power Generation and Consumption
- Deal with flexible crew schedules

- Control Goals: For appropriate size of buffers maintain cabin
- O2 and CO2 levels + temperature
- & provide adequate clean water supply at specified levels to support
- crew habitat + EVA activities
- Ensure closed loop operation (minimum waste) of resources while not exceeding power (energy) requirements

- Details: Lunar Reference Mission Document (Hanford and Ewert)

## Evaluating System Performance90 Day Mission

- Potable water: Initial: 650 liters; End: 200 liters

- Energy stored: Min: 200 kW-hour; Max: 1300 kW-hour

- Oxygen tank: Initial = 9.9 kg; Max = 10 kg; Min = 9.9 kg

- CO2 tank: Initial = 0 kg; Max = 2.6 kg; Min = 1.4 kg

**Dynamic modeling allowed robust controller design**
**But key finding:  System required much smaller buffers**
**Overall reduced Equivalent System Mass (ESM)**

## Long-term Issues

**Process**

**Behavior**
**Monitors**
**&**
**Diagnoser**

**Fault-adaptive**
**Controller**

**Control Loop**

**Resource**
**monitors**

**Planner**
**&**
**Scheduler**

**Human(s)**

**Decision Making Loop**

**Supervisory**
**Controller**

- Feedback
- Control

**ISHM**

**Short-term**
**issues**
- (keep system
- safe & operational)

**Long-term**
**issues**
- (focus on mission goals & needs)

**Prognosis**
**system**

**Long-term Issues**
** ****Planning, Maintenance & Control**

## Resource monitors

- From Behavior (and Function) to Performance Monitoring
- Examples: Monitor power consumption, rate of generation of product
- Typically, these changes will be small and subtle & accumulate over time
- Key issue: how to project consequences of subtle (small) changes on behavior, then long-term performance and resources available for mission
- Need ability to monitor + predict, i.e., Prognosis
- ISHM extends resource monitoring + prognosis to  decision making
- Decision making implies actions to correct anomalies, e.g., maintenance, repair, reconfiguration
- With and/or without humans in the loop

## Integrated Planning & Control Architecture

- Model Information Interface

- ALS

- Crew and habitat

- Local Controllers

- System Controllers

- Supervisory Controller

- Mission
- Control
- (Earth Station)

- World model

- Sequencer

- Planner

- System State Information Interface

- Crew and system components state

- Plan and tasks state

- mission state

- Commands and schedules

- Task/plan
-  feasibility

- Mission specs and requirements

- Current
- measurements

- ALS World model interpreter

- ALS dynamic model interpreter

- set-points,
- constraints

- Plan evaluation

- Periodic Plans/tasks

- Crew
- (Earth Station)

## Example: Planning + Control

- 90 day mission with 28 day cycles
- Phase 1:
- Startup
- EVA on day 18
- First generate 28 day plan
- Initialization + testing activities
- Science expts. startup
- Build up buffers to required levels

**Planner**
- 7 days startup
- 4 days – high CO2 consumption
- 4 days – high CO2 state to scrub system
- 1 day – O2 preparation for EVA
- Normal operations from day 10
- EVA on day 18
- Maintenance checks day 19-20
- Normal operations day 20-28

- Dynamic Control Executive Takes Over

## Example: continued

- Day 10 – Anomaly detection & analysis: Restriction in CO2 output from CDRA + leak in dessicant bed
- Controller: Restrict CRS + OGS operations
- Report to Planner -- CO2 clear up needs to 5 days
- Question:
- (i) perform  2 day CDRA repair – creates O2 restriction
- (ii) push EVA from cycle to day 20
**Mission control + crew – cannot push back EVA**
**Planner + Controller solution:**
**Crew give up exercise period – from day 9 to 20**
**EVA on day 18**
**CDRA repair days 19 & 20**
**Repair procedures chosen by**
**	****sequencer**
**System state, models updated**
**Planner suggests return to normal ops**
**Controller concurs**

## Issues in ISHM & System design

- ISHM does not (just) imply autonomy – ISHM has an important role in humans-in-the loop systems (crew, mission control)
- Apollo 13 scenario – faster response
- ISHM is not just to deal with failures – it should be maintaining and optimizing nominal + degraded operations
- Resource allocation
- Reduction in mission costs (ESM)
- An Approach: Simulation test-beds that are based on systematic modeling technologies
- Contribute to more efficient, reliable, and safe design
- Address system integration issues (hardware–hardware, hardware–software)
- Tools for “what-if” (scenario) analysis
- Variety of other analysis tools that can be used by mission controllers and crew during missions

**Focus: Decision Support first and primary;  Autonomy secondary**

## Current and Future Applications

- Crew Exploration Vehicle
- Air, Water, Waste & Power systems – does not have to be completely closed-loop
- Other subsystems of the CEV
- Deal with partial shut down during uncrewed operations (e.g., while crew on lunar surface) and startup
- Lunar Habitats
- Move toward closed loop air and water
- Resource monitoring important: link to scheduling and operations
- Mars Vehicles and Habitats
- All components  including biomass systems important
- Closed loop operations
- Resource and health monitoring, scheduling, predictive analysis, control, maintenance, and prognosis will be key to success of such missions

**Number of design and run-time metrics will have to be addressed**
**One of the more important ones – Equivalent System Mass (ESM)**