LabView implements most of the mentioned algorithms, some come with tutorials and toolkits, some are white papers, others are programs offered from third parties. Delight yourself with a "Labview <algorithm>" search on your favorite web browser. Note: <algorithm> is generic, insert PID, FUZZY, GENETIC and etc
In the desin of complex control systems with high reliability indices on the spec, such as a nuclear energy powered submarine, safety is integrated across the board on all phases. However, some of the basic design functions stay from time to time with the team of engineers who focus more on the crude functionality of the various processes.
@snandu13 "Is the logic built in Fuzzy logic only in Software? I donot know how Fuzzy Logic is built into the controllers."
You can implement any form of logic in either software or hardware -- a software implementation is more versatile with regard to changing it -- and it can be a lot easier to capture your "intent" -- but a hardware implementation will always be much faster (orders of magnitude in many cases) and consume much less power...
@Clive Maxfield- Ok, I think that I am starting to understand this a little bit better. Add me to the list of people asking you for more book references on this. Thanks again for another great lecture.
@KevinJam: "Saftey system as in the safety Instrumented systems to implement safety functions on the Basic process controll loop is normally handled as an independent network to avoid potentially common cause failure."
Saftey system as in the safety Instrumented systems to implement safety functions on the Basic process controll loop is normally handled as an independent network to avoid potentially common cause failure.
yeah, I know how to see exactly how many points I have for each track, but like I said, I have 22 points for the first track, and I thought I watched everyday. Is there anyway to see the point breakout per lecture instead of per track?
@clia "@Clive Maxfield - So, is GA something that would be most apt to use when not looking for immediate responses?"
I would say you've nailed it -- you use GA to quickly find an optimal solution amongst an almost infinite solution space -- once you have that solution you run with it.
But they you have th efact that in a complex system the problem itself (for example the surrounding environment) may change over time ... in which cas eyo umay wish to have an adaptive system -- and the way th esystem adapts may be based on GA techniques...
@jrjohns: "Given the non-deterministic nature of GA, it seems unlikely that you will see GA used in critical safety systems (or is there a way to get this type of system approved?)"
At the moment I think GA is more of interest in coming up with optimal solutions to a system -- by which I mean more in setting the system up -- as opposed to being used "on th efly" while the system is running
the best approach is to understand the nature of the type of process being controlled / its inherent behaviour before choosing a control strategy...it is possible you may well compose a combination of stragy approaches
Max: Actually, the notion of model based design is not only inherant to Model Predictive Control, but has been with P, PD, PID since before the II world War in practical applications such as syc machine control and rocket launching and navigational control.
@MaxianLab: an event occurs at a point in time and then is over, but a state is a condition of the system which can change the interpretation of incoming events. For example, a switch closure would be an event and might or might not cause a state change. Initialization might be a state in which such switch closures are ignored, while normal operation might be a state where the switch closures are detected and responded to somehow (perhaps with a change to yet another state).
You haven't really programmed a computer until you have set at a console with 24 switches to set the 0s and 1s for a word and pushed another switch to enter each word in memory before running the program.
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In a bid to boost the viability of lithium-based electric car batteries, a team at Lawrence Berkeley National Laboratory has developed a chemistry that could possibly double an EV’s driving range while cutting its battery cost in half.
Using Siemens NX software, a team of engineering students from the University of Michigan built an electric vehicle and raced in the 2013 Bridgestone World Solar Challenge. One of those students blogged for Design News throughout the race.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.