Control over Wireless Networks

Transcription

1 Wireless control Control over Wireless Networks Sensors Controllers Actuators Karl Henrik Johansson School of Electrical Engineering Royal Institute of Technology Stockholm, Sweden CTS-HYCON Workshop, Université Paris Sorbonne July 2006 Plant Wireless control Wireless control s everywhere Sensors Controllers Actuators Machine-to to-machine device population forecast Trillion 500 Billion Microprocessors: bits CPU s etc. RFID/Sensors: Location Humidity Temperature Vibration Liquid Weight etc. 2 Billion 1 Billion Info Devices: Smart Devices: Appliances Machinery Vehicles Bldg. Eqpt. etc. Plant 300 Million PC s: Mobile Phones PDA s Web Tablets etc. Forecast of installed base, 2010 The FocalPoint Group, LLC

2 Control of the SMART-1 1 spacecraft Hybrid control of orbit and attitude First European lunar mission, launched Sep 2003 Go to the moon using electric primary propulsion Thrust 68 mn, 410 days to reach moon orbit Moon capture Detumble Mode Safe Mode Sun sensors (3 in total) Star trackers (2 in total) Reaction wheels (4 in total) Hydrazine thrusters (4 in total) EP thruster and orientation mechanism Switch between different control configurations depending on commands and autonomous actions Bodin, Swedish Space Agency, 2005 Architecture of SMART-1 1 spacecraft Architecture of SMART-1 1 spacecraft A networked control with tight interactions between control s and other units Networked control architecture gives efficient development and flexible operation Wired and wireless communication s influence control performance Power Control Earth communication Control computers Actuators Sensors Payload Power Earth communication Sensors Actuators Payload Network Karl H. Johansson, CTS-HYCON Workshop, Université Bodin, Paris Swedish Sorbonne, Space 2006 Agency, 2005

3 Audio Crash safety Automatic climate control Auxiliary heater water-to-air Auxiliary heater air-to-air Clock and timer Road transport informatics gateway Road transport informatics Coordinator Gearbox management Articulation control Locking and alarm All wheel drive Instrument cluster Tachograph Visibility Air prosessing Body work Body chassis Engine management Exhaust Emission Control Brake management Suspension management t Suspension management dolly t Illustrate through applications, research problems and potential solutions New functionality Wireless information s for improved fuel efficiency in vehicles Predict road and driving conditions based on wireless information s Congestion info through RDS, digital maps, GPS Control vehicle subs to improve fuel efficiency Cruise control, automated gear shifting, auxiliary s Networked control architecture in Scania truck AUS CSS ACC WTA ATA CTS RTG RTI Green bus Yellow bus COO 1 Diagnostic bus Bus GMS LAS AWD ICL 1 TCO VIS 1 APS BWS BCS 2 Red bus ACS 2 EMS 1 EEC Body Builder Truck Body Builder ISO11992/3 BMS 15-pole Trailer 7-pole SMS ISO11992/2 SMS Suspension management SMD SMS Suspension management

4 Optimal control of cooling based on road profile ahead and predicted driver Charge air cooler Radiator Thermostat T Fan Fan clutch M Retarder Optimal control of cooling based on road profile ahead and predicted driver Charge air cooler Radiator Thermostat T Fan Fan clutch M Road profile Retarder Coolant temp States x 1 cooling temp x 2 state of charge Inputs u 1 pump speed u 2 fan speed u 3 generator power External influences v 1, v 2 heat v 3 speed v 4 el. consumption water air heat electricity Energy buffer _ + Pump Engine M G Generator Other consumers [Pettersson & J, 2006] States x 1 cooling temp x 2 state of charge Inputs u 1 pump speed u 2 fan speed u 3 generator power External influences v 1, v 2 heat v 3 speed v 4 el. consumption water air heat electricity Energy buffer _ + Pump Engine M G Generator Other consumers Fan & pump speed Energy [Pettersson & J, 2006] Reduce maintenance through wireless Remove cabling Communication cabling in robots is subject to heavy wear and therefore requires frequent maintenance Replace wires between robot controller and gripper through wireless communication Removing cables undoubtedly saves cost, but often the real cost gains lie in the radically different design approach that wireless solutions permit. [ ] In order to fully benefit from wireless technologies, a rethink of existing automation concepts and the complete design and functionality of an application is required. Jan-Erik Frey, ABB Wireless Actuator Sensor Interface

5 Local rules for global properties Distributed coordination of large set of agents Analyze scalability How does consensus algorithms scale with network size? ensus under symmetries ensus under symmetries [Carli et al., 2006; Speranzon, 2006] Trade off between communication and performance: Static symmetric communication graphs gives slow convergence Random graphs gives faster convergence [Carli et al., 2006; Speranzon, 2006]

6 Network-aware control architecture Compensate network variations Controller should adapt to changing network conditions Estimate network states Network delay Data loss probability Bandwidth Wireless network Control law Network observer Plant observer Delay estimation Controlled data loss Internet round-trip time (RTT) data are noisy with piecewise constant average Complex network dynamics hard to model RTT estimation in TCP: Improved estimation thru Kalman filter with hypothesis test (CUSUM filter) Compensate data loss through added redundancy Base amount of redundancy on feedback information from decoder Adaptive forward error correction [Jacobsson et al., 2004]

7 Controlled data loss Extremum-seeking control of redundancy: Track network variations through variable redundancy [Flärdh et al., 2005] Efficient control strategies Control under limited communication and sensor resources Objective: Attenuate disturbances while limiting sensor transmission (to extend lifetime and avoid congestion) Encoder-decoder decoder design for event-triggered triggered feedback control over bandlimited channel Optimize closed-loop performance based on plant model and disturbance statistics Approach: Event-based sensing with optimal use of communication bandwidth Remarks Don t fix it, if it ain t broken (Åström) Periodically sampled sensors may waste resources Uniform quantization is seldom optimal Communication Optimize encoder (encoder regions) and decoder (reconstruction points) [Bao et al., 2006]

8 Encoder-decoder decoder design for event-triggered triggered feedback control over bandlimited channels Plant output Train encoder and decoder through sequential Monte Carlo estimation Control signal Illustrate through applications, research problems and potential solutions [Bao et al., 2006] Conclusions Acknowledgementss Control over wireless networks has a growing domain of application, e.g., industrial automation, vehicle control Several open research problems related to architecture, complexity, reliability and security Need for integrated approaches: Control-aware networking Network-aware control Challenge traditional methodologies in control and communication Slides and papers at Presented work was done together with colleagues and students at KTH: Lei Bao, Carlo Fischione, Oscar Flärdh, Håkan Hjalmarsson, Krister Jacobsson, Mikael Johansson, Magnus Lindhé, Niels Möller, Niklas Pettersson, Per Sahlholm, Mikael Skoglund, Alberto Speranzon Financially supported by Swedish Research Council Swedish Foundation for Strategic Research Swedish Programme Council for Vehicle Research European Commission IST 6th Framework Programme RUNES HYCON RUNES