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Papers by jian wan

IFAC Proceedings Volumes, 2004

The optimization problems of nonlinear model predictive control are generally non-convex and thei... more The optimization problems of nonlinear model predictive control are generally non-convex and their convergence to global optima can hardly be assured. In this paper, interval analysis is applied to such non-convex optimization problems by taking advantage of its guaranteed numerical nature of global optimization and constraint satisfaction. Simulation result demonstrates the feasibility of applying interval analysis to discrete-time nonlinear model predictive control.

IEEE Transactions on Semiconductor Manufacturing, 2018

Incorporating virtual metrology (VM) into run-torun (R2R) control enables the benefits of R2R con... more Incorporating virtual metrology (VM) into run-torun (R2R) control enables the benefits of R2R control to be maintained while avoiding the negative cost and cycle time impacts of actual metrology. Due to the potential for prediction errors from VM models, the prediction as well as the corresponding confidence information on the predictions should be properly considered in VM-enabled R2R control schemes in order to guarantee control performance. This paper proposes the use of Gaussian process regression (GPR) models in VM-enabled R2R control due to their ability to provide this information in an integrated fashion. The mean value of the GPR prediction is treated as the VM value and the variance of the GPR prediction is used as a measure of confidence to adjust the coefficient of an exponentially-weighted-moving-average (EWMA) R2R controller. The effectiveness of the proposed GPR VM-enabled R2R control approach is demonstrated using a chemical mechanical polishing process case study. Results show that better control performance is achieved with the proposed methodology than with implementations that do not take prediction reliability into account.

IEEE Robotics and Automation Letters, 2019

This paper develops a geometrical construction of the shortest Dubins path in a discontinuous ori... more This paper develops a geometrical construction of the shortest Dubins path in a discontinuous orientation-restricted environment. The method proposed here builds the shortest path from one pose to the other while avoiding a no-go zone in terms of orientation, and being constrained to move forward. Finally, an application to autonomous sailboats is then provided to validate the feasibility of the planned shortest path in a position keeping scenario.

IEEE Transactions on Automatic Control, 2018

This paper proposes a new set-membership technique to implement polytopic set computation for non... more This paper proposes a new set-membership technique to implement polytopic set computation for nonlinear discrete-time systems indirectly. The proposed set-membership technique is applied to solve the guaranteed state estimation problem for nonlinear discrete-time systems with a bounded description of noises and parameters. A common practice for this problem in the literature is to search an optimal zonotope to bound the intersection of the evolved uncertain state trajectory and the region of the state space consistent with the observed output at each observation update. The new approach keeps the polytopic set resulting from the intersection intact and computes the evolution of this intact polytopic set for the next time step through representing the polytopic set exactly by the intersection of zonotopes. Such an approach avoids the overapproximation bounding process at each observation update, and thus, a more accurate state estimation can be obtained. An illustrative example is provided to demonstrate the effectiveness of the proposed guaranteed state estimation via indirectly implemented polytopic set computation.

IFAC Proceedings Volumes, 2011

The set-point tracking of certain process variable trajectories is often needed for the lower lev... more The set-point tracking of certain process variable trajectories is often needed for the lower level control in batch processes so as to achieve desirable final product quality for the higher level control. In order to realize trajectory tracking successfully, process models should be known in advance. In fact, process models play an essential role in trajectory tracking. Due to the difficulty for developing first-principle models for batch processes, empirical models such as multi-way principal component analysis (PCA) and multi-way partial least squares (PLS) are increasingly used in practice. Trajectory tracking using multi-way PCA models has been proposed in the literature, where the underlying optimizations are performed in the latent variable space. This paper explores the corresponding application of multi-way PLS models for the task of trajectory tracking and compares it with the existing multi-way PCA model-based methods through benchmark case studies.

Proceedings of 2012 UKACC International Conference on Control, 2012

The control of exothermic chemical batch reactors has received much attention in literature over ... more The control of exothermic chemical batch reactors has received much attention in literature over the years for their increasing importance in manufacturing industries and also the unique quality control challenges that they provide. However, most of the control schemes proposed to deal with these challenges make use of models that implicitly control the product quality. For example it is assumed that a control scheme that successfully regulates the reactor temperature along an apriori calculated optimal profile should imply satisfactory quality trajectory control. In this paper it is shown that this assumption is not robust enough to deal with some kinds of disturbances that may occur during the batch. It is also shown that product quality control can be greatly improved by proposing a new control scheme that makes use of NIR spectroscopic measurements as feedback information for a quality control system. The results of two controllers using this scheme are compared with a more widely used implicit control strategy in two test cases with unmeasurable system disturbances.

IFAC Proceedings Volumes, 2014

A practical strategy for controlling batch product quality evolution by means of latent variable ... more A practical strategy for controlling batch product quality evolution by means of latent variable models and intermittent measurements is presented. The methodology is based on the identification of data-based models using multivariate statistical methods such as Partial Least Squares (PLS). PLS is able to identify models with a reduced number of latent variables, which account for most of the process variability. The data-based models are employed along with a moving window strategy in order to predict product quality throughout the batch operating time. The predictions can be utilized within a Model Predictive Control (MPC) architecture so that trajectory tracking control can be directly applied to batch product quality. A simulated example of fed-batch aerobic growth of Saccharomyces Cerevisiae is used to demonstrate the capabilities of the proposed trajectory tracking controller.

World Automation Congress, 2004

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot... more This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically

ISA Transactions, 2014

Batch processes are commonly characterized by uneven trajectories due to the existence of batchto... more Batch processes are commonly characterized by uneven trajectories due to the existence of batchto-batch variations. The batch end-product quality is usually measured at the end of these uneven trajectories. It is necessary to align the time differences for both the measured trajectories and the batch end-product quality in order to implement statistical process monitoring and control schemes. Apart from synchronizing trajectories with variable lengths using an indicator variable or dynamic time warping, this paper proposes a novel approach to align uneven batch data by identifying shortwindow PCA&PLS models at first and then applying these identified models to extend shorter trajectories and predict future batch end-product quality. Furthermore, uneven batch data can also be aligned to be a specified batch length using moving window estimation. The proposed approach and its application to the control of batch end-product quality are demonstrated with a simulated example of fed-batch fermentation for penicillin production.

A general framework for computing polytopic robust controllable sets of constrained nonlinear unc... more A general framework for computing polytopic robust controllable sets of constrained nonlinear uncertain discrete-time systems as well as controlling such complex systems based on the computed polytopic robust controllable sets is introduced in this paper. The resulting one-step control approach turns out to be a robust model predictive control scheme with feasible unit control horizon and contractive constraint. The solvers of set inversion and constrained minimax optimization via interval analysis are applied to compute robust controllable sets and one-step control inputs in a reliable way. The computed robust controllable sets are unions of boxes and polytope geometry is applied to approximate a union of boxes innerly by one polytope.

IET Cyber-Systems and Robotics, 2019

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The essence of MPC is to avoid solving the Hamilton-Jacobi-Bellman equation by repetitively solvi... more The essence of MPC is to avoid solving the Hamilton-Jacobi-Bellman equation by repetitively solving an open-loop optimal control problem instead, which offers the significant ability to treat input and state constraints explicitly at each step. Additional contractive constraint is usually needed to be incorporated into the open-loop optimization for guaranteeing the stability of the closed-loop system. The resulting online constrained optimization must be fulfilled within the time constraint imposed by the sampling time of an application. Thus computational reliability and efficiency are two critical issues in applying MPC, especially in applying nonlinear MPC, where normally complex nonlinear programming problems are concerned. The thesis aims to explore computationally reliable and efficient approaches of contractive MPC for discrete-time systems. Two types of contractive MPC have been studied: MPC with compulsory contractive constraint and MPC with a contractive sequence of controllable sets. Techniques based on convex optimization and interval analysis are applied to deal with linear and nonlinear contractive MPC, respectively. Classical interval analysis is extended to zonotopes in geometry for designing a terminal control invariant set in the dual-mode approach of MPC. It is also extended to modal intervals in modality for computing robust controllable sets with a clear semantic interpretation. The tools of convex optimization and interval analysis have been combined further to improve the efficiency of contractive MPC for various kinds of constrained nonlinear uncertain discrete-time systems. Finally, the addressed two types of contractive MPC have been applied to control a Micro Robot World Cup Soccer Tournament (MiroSot) robot and a Continuous Stirred-Tank Reactor (CSTR), respectively.

ESAIM: Control, Optimisation and Calculus of Variations, 2009

A general framework for computing robust controllable sets of constrained nonlinear uncertain dis... more A general framework for computing robust controllable sets of constrained nonlinear uncertain discrete-time systems as well as controlling such complex systems based on the computed robust controllable sets is introduced in this paper. The addressed one-step control approach turns out to be a robust model predictive control scheme with feasible unit control horizon and contractive constraint. The solver of 1-dimensional quantified set inversion in modal interval analysis is extended to 2-dimensional cases for ...