I would think (depending on the exact structure of your "Linux/PHP" site,) that you essentially have three main options.
Using an existing (non-PHP) IR/search system
You could (as suggested in @Charles's answer) use something like ElasticSearch, or host your own Lucene (https://lucene.apache.org) or Sphinx environment.
Unfortunately, these solutions have some fairly hefty drawbacks (particularly if your site is somewhat small):
You will need to provide these various engines with an index. Which may (depending on your application), be as simple as munging an RSS-feed of 'posts' or 'pages' etc. But it could also be fairly complex, if you have a large site with no underlying structure/DB to get index data from.
These search engines will need to be hosted, either on a VPS, other server or (as with ElasticSearch) some SaaS platform. This would obviously add additional expense to your efforts.
Implement (or plug-in) a tag-based search
Tag based searching (ala SE), may be easier as it allows your users to construct the index for you. Whenever a member tags something, it gets added to a database which can then be searched for the member search.
The obvious cons here are that:
This burdens your users with the construction of the index, which may harm reliability, etc.
Searching for tags and doing full text search are very different things. Your members may miss a lot of untagged results which may be relevant.
However, on the plus side this is probably cheaper than the first option, and may be quicker to implement than the next.
Roll-your-own crawler/spider to make an index
As you seem to be eluding to in your comment, you could use wget, curl or PHP's file_get_contents function to retrieve your own website's URL's (with some request flag or cookie to get member's area access).
Although it may seem clunky (fetching your own content), this may be easier than constructing an index yourself if there's no underlying database or model for something like Lucene to use.
Once retrieved you then just need to tokenize the data and store it in something like a database or other form of index.