Local shape control methods,such as B-Spline surfaces, are well-conditioned such that they allow high-ﬁdelity design optimisation, however this comes at the cost of degraded optimisation convergence rate as control ﬁdelity is reﬁned due to the resulting exponential increase in the size of the design space. Moreover, optimisations in higher-ﬁdelity design spaces become illposed due to high frequency shape components being insuﬃciently bounded; this can lead to non-smooth and oscillatory geometries that are invalid both in physicality (shape) and discretisation (mesh). This issue is addressed here by developing a geometrically-meaningful constraint to reduce the eﬀective degrees of freedom and improve the design space thereby improving optimisation convergence rate and ﬁnal result. A new approach to shape control is presented using coordinate control(x,z) to recover shape-relevant displacements and surface gradient constraints to ensure smooth and valid iterates. The new formulation transforms constraints directly onto design variables, and these bound the out-of-plane variations to ensure smooth shapes as well as the in-plane variations for mesh validity. Shape gradient constraints approximating a C2 continuity condition are derived and demonstrated on a challenging test case: inviscid transonic drag minimisation of a symmetric NACA0012 aerofoil. Signiﬁcantly the regularised shape problem is shown to have an optimisation convergence rate independent of both shape control ﬁdelity and numerical mesh resolution, while still making use of increased control ﬁdelity to achieve improved results. Consequently, a value of 1.6 drag counts is achieved on the test case, the lowest value achieved by any method.