P. Albertos* & A. Crespo + Universidad Politécnica de Valencia * Dept. of Systems Engineering and Control, + Dept. of Computer Engineering POB E Valencia, Spain. Fax: Embedded Control Systems: Control Kernel

NoE on Embedded Systems Design ©P. Albertos 2005 Embedded Control Systems Embedded systems with: – hard RT constraints – guarantee of safe operation – best possible performances Additional issues from viewpoint of: – implementation – computation – algorithmic

NoE on Embedded Systems Design ©P. Albertos 2005 RT Control Issues RT Constraints: –Maximize the time determinism For many controllers a worst-case approach works well e.g., PI, PID, State Feedback, … however, many exceptions: hybrid controllers that switch between different modes with different characteristics model-predictive controllers (MPC) convex optimization problem solved every sample execution time can vary an order of magnitude –Compensate the variations: Measure and react Feedback robustness

NoE on Embedded Systems Design ©P. Albertos 2005 Control requirements Multiloop control Non-uniform sampling Missing data Variable delays Sampling period changes Mode changes Fault tolerant Safe operation CPU optimization Battery control Process to control Environment ECS CPU Batt ery S1S1 SiSi Memory A1A1 AiAi

NoE on Embedded Systems Design ©P. Albertos 2005 ECS: Implementation The same resources must be shared between different tasks Alternative control algorithms should be ready to get the control of the process Working conditions, such as priority, allocated time and memory or signals availability may change Variable delays should be considered Validation and certification

NoE on Embedded Systems Design ©P. Albertos 2005 ECS: Computational viewpoint Economic algorithms Information updating Optional tasks Hybrid systems CPU use measurement and optimisation On-line scheduling Memory saving Economic hardware redundancy Fault detection and isolation

NoE on Embedded Systems Design ©P. Albertos 2005 Control Performances RT Constraints: –Maximize the time determinism For many controllers a worst-case approach works well e.g., PI, PID, … however, a lot of exceptions: hybrid controllers that switch between different modes with different characteristics model-predictive controllers (MPC) convex optimization problem solved every sample execution time can vary an order of magnitude –Compensate the variations: Feedback robustness Measure and counteract Relevance of the control actions The Control Effort concept Sensitive to time delays Changes in the sampling period: –Controller parameters –Past data Commutation bumping

NoE on Embedded Systems Design ©P. Albertos 2005 MIMO controlled plant ref H j.... yiyi ujuj vjvj zi zi SiSi Process Control Integrity Redundancy Performance degrading

NoE on Embedded Systems Design ©P. Albertos 2005 ECS: Control algorithm viewpoint –Reduced order models –Non-conventional sampling and updating patterns –Missing data control –Event-triggered control –Hybrid control systems –Decision and supervisory control –Multimode control –Sampling rate changes –Fault-tolerant control –Degraded and back-up (safe) control strategies –Battery monitoring and control

NoE on Embedded Systems Design ©P. Albertos 2005 The kernel concept Basic services: –Task and time management –Interrupt handling –Interface to the applications (API) –Mode changes –Fault tolerance OS kernel: Additional services –File management –Quality of service –Tracing and debugging –Mode changes –Fault tolerance

NoE on Embedded Systems Design ©P. Albertos 2005 The OS kernel (I) The OS Kernel provides the minimal services that should be included in any embedded system. Task management and synchronization mechanisms Task communication Semaphores and monitors Server definition (aperiodic servers, constant bandwidth servers)) Scheduling policies Time management Real-time clock High resolution timers and execution timers (limit the cpu use per task) Absolute and relative delays Application interface (API) POSIX (standard) OSEK (automobile industry specification) ….

NoE on Embedded Systems Design ©P. Albertos 2005 The OS kernel (II) The OS Kernel provides the minimal services that should be included in any embedded control system. Fault tolerance Degrade task activity (when a task does not guarantee some timing constraints, the degraded behavior is executed) Change mode events raised when some faults can not be managed. Mode changes Mode definition (set of tasks associated to a mode) Mode change events (event to change from one mode to another) Mode change protocol Security Network access Attacks

NoE on Embedded Systems Design ©P. Albertos 2005 The OS kernel (III)

NoE on Embedded Systems Design ©P. Albertos 2005 The Control Kernel concept Ensures control action (CA) delivering Data acquisition of major signals Transfer to new control structure Additional CA computing facilities Communication facilities Coordination facilities DE driven-control

NoE on Embedded Systems Design ©P. Albertos 2005 Event-driven control

NoE on Embedded Systems Design ©P. Albertos 2005 Basic Control Loop CT DT

NoE on Embedded Systems Design ©P. Albertos 2005 Basic Control Loop

NoE on Embedded Systems Design ©P. Albertos 2005 Control Kernel Ensures control action (CA) delivering –Safe (back-up) CA computation –Safe CA computation based on previous data Data acquisition of major signals –Safe CA computation based on current data Transfer to new control structure –Basic control structure parameters computation –CA computation Full DA –Control structures evaluation and selection –CA computation (different levels) Communication facilities Coordination facilities

NoE on Embedded Systems Design ©P. Albertos 2005 The control kernel concept Plant CA deliv Backup CA CA user CA computation DA Safe operation in any condition

NoE on Embedded Systems Design ©P. Albertos 2005 Control Kernel Algorithm CA delivering Backup CA Backup CA Computation Current safe b-up CA comp. Basic CA computation CA comp CA comp. (Process model) –Essential –Partial –Complete

NoE on Embedded Systems Design ©P. Albertos 2005 Control Kernel Algorithm Model reduction: –Partial control (parts of the plant) - Partial phenomena (fast/slow dynamics) S1 S2 u y

NoE on Embedded Systems Design ©P. Albertos 2005 Conclusions Control Kernel Variables relevance –Control effort