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%252C+an+advanced+approach+integrating+Gaussian+process+(GP)+with+model+predictive+control+(MPC)+for+enhanced+control+in+complex+systems.+It+begins+with+GP+regression+fundamentals%252C+illustrating+how+it+enriches+MPC+with+enhanced+predictive+accuracy+and+robust+handling+of+uncertainties.+A+central+contribution+of+this+tutorial+is+the+first+detailed%252C+systematic+mathematical+formulation+of+GP-MPC+in+literature%252C+focusing+on+deriving+the+approximation+of+means+and+variances+propagation+for+GP+multi-step+predictions.+Practical+applications+in+robotics+control%252C+such+as+path-following+for+mobile+robots+in+challenging+terrains+and+mixed-vehicle+platooning%252C+are+discussed+to+demonstrate+the+real-world+effectiveness+and+adaptability+of+GP-MPC.+This+tutorial+aims+to+make+GP-MPC+accessible+to+researchers+and+practitioners%252C+enriching+the+learning-based+control+field+with+in-depth+theoretical+and+practical+insights+and+fostering+further+innovations+in+complex+system+control.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.27b48c25a715874f8465d514230073e8%3frik%3dO4MhIbv1lXmErw%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Model+Predictive+Control+Tutorial&FORM=IRPRST&ck=1FFAC076B995658DF204345F3663145E&selectedIndex=78&itb=0)
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