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Architecture of Intelligent Systems - 2. 1. Plan Analysis of a Physical system with simple control function Complex system and Abstraction Mapping of the physical system to the Intelligent system. 2. Sensor. Reference. Signal Conditioning. Comparator. Error signal. Corrector.
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Plan • Analysis of a Physical system with simple control function • Complex system and Abstraction • Mapping of the physical system to the Intelligent system 2
Sensor Reference Signal Conditioning Comparator Error signal Corrector Cold air Control signal Correction signal Controller Actuator Controller Physical system - Room with A/C 3
Sensor Sensor signal Controller Reference value or Control parameters Cold air Control signal Actuator Physical system - A/C Room 4
Intelligent system Actuator Sensor Is IS a controller? Environment 5
IS is some sort of controller (or at least a controller and may be more) Intelligent system Controller Actuator Sensor Environment 6
Can there be more than one sensor and one actuator in a system? • What other actions are needed in our IS as a result of multiple sensors? • Guess what type of sensors, actuators and controls would you like to have in our crazy car – 4 independent wheel drive car! • Would our simple controller be sufficient for our car?
There can be many sensors, actuators and • controllers • Coordinate the actuators • The information from multiple sensors is • to be analysed and control actions for • each actuator are to be identified, control • parameters and control actions are to be • generated. • The model of the environment (world • model) is to be generated. • Error handling information is to be • incorporated
Thus the system looks like World model Controller Signal Analyser coordinator Sensors Actuators Controller Controller Controller ? ? ? Environment
Crazy car Sensors for indicating the direction and speed of each wheel User communication interface Task identification and its decomposition Control signal generation Coordinate the control signals at the actuators Model for the actions of the wheels Sensors for the proximity and speed of other cars and its own speed World model for taking decisions regarding collisions and collision avoidance Knowledge base and expert advice for taking decisions
How should we build our Intelligent system? Do we need to pack all the features into a single monolithic program or should we build up a modular / layered product? Remember all complex programs are modular/layered - OS How many layers? Suggest three based on management model – execution level, coordination level, executive level. But could be as many as we like.
coordination level Execution level Top management & Executive level Sensors Actuators High level management Environment Low level management Middle level management
Low Middle High Human operators Sensors Data flow/ response Physical system Commands Actuators Human interventions (in red) Functional Architecture of Intelligent (control) system Centralised Vs Distributed Is it technology dependent?
Low level Or execution level control manager Signal conditioning, sampling, holding, buffering, multiplexing and demultiplexing, queuing, scheduling of data acquisition & actuators, data supply to controllers, control parameter generation, error detection and send error information to appropriate units, Algorithms in HW & SW Execution of control Multiple sensor information, multiple controllers Multiple copies of HW & SW Commn with middle level Sensor information Human interventions signals to actua tors
Middle level Or coordination level control manager Coordination, Synchronisation, timing signals, Prioritisation and sequencing, Monitoring sys health & processes, decision making, capability assessment, fault assessment and analysis, system & environ model generation & updating, learning, Task analysis, Task decomposition, planning for execution, Resource management, algorithm development, Knowledge bases, logic resolution, Algorithm development, simulations Interface between the low level &high level, limited copies of HW & SW Commn with high level Commn with low level Human interventions
High level Or organisational manager Goal assessment and generation, Goal analysis, goal to task conversion, Strategising, planning to achieve goals, consequence evaluation, decision making, User I/F, feasibility analysis and capability assessment, learning knowledge bases, data mining, Single copy Commn with middle level Human interventions and commn with humans
KB Mu x Signal Condi tioning Digitisers Sensors Info buffer/ storage/anal P h y s i c a l s Y s Decision making unit (Int control) Refe rence Data Switch Commn with middle level DB KB Sys state & adaptive parameters Timer Human interventions Load algos Actua tors Contro llers D e Mux Err cor Fault info analyser Low level control details KB Instructions, commands, algorithms
Synchroniser Scheduler Designer KB DSS From data switch Sim/mod Commn. with Exe cutive Level Info Assessor Control Implementation supervisor Control Manager (Task anal) From System State model Algos, commands, instructions Math model Algo developer Algo Repository Planner KB Sim Human inter vention From Fault info anal Plan selector Plan generator Fault Supervisor Sim KB KB Plan repository Fault info
Commn. from Human operators Strategiser Command Interpreter Task generator/ goal analyser Comma nds, & tasks Goal generator KB and Data warehouse Build model Capability/ feasi bility assessor System model Fault info Informa- tion formatter and presenter Simulator Info/ Messa ges to human operators Identification of problems & solutions Soln. opti miser DSS Info generator Decision on action