Most practical control problems must deal with constraints imposed by equipment limitations, safety considerations or environmental regulations. While it is often beneficial to maintain operation close to the limits in order to maximize profit or meet stringent product specifications, the violation of actuator constraints during normal operation can result in serious performance degradation (sometimes instability) and economic losses. This thesis is concerned with the development of control strategies for multivariable systems which systematically account for actuator constraints while guaranteeing closed-loop stability as well as graceful degradation of non-linear performance. A novel anti-windup structure is proposed which combines the efficiency of conventional anti-windup schemes with the optimality of model predictive control (MPC) algorithms. In particular, the classical internal model control (IMC) law is enhanced for optimal performance by incorporating an on-line optimization. The resulting control scheme offers both stability and performance guarantees with moderate computational expense. The proposed optimizing scheme has prospects for industrial applications as it can be implemented easily and efficiently on programmable logic controllers (PLC).